Unico Connect Private Limited

Senior Backend Engineer

Node.js, System Design & Production Platforms

📍 Mumbai (On-site) | Full-time | 5+ years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior Backend Engineer to own the backend architecture of a complex production AI platform on a dedicated client engagement: API design and data modelling, multi-tenancy, orchestration of long-running agent workloads, and the services that manage user projects and generated output.

We are open to full stack engineers whose primary strength and interest is backend. If you have shipped full stack work but the backend is where you do your deepest engineering, you are a fit for this role.

The mandatory requirement for this role is hands-on production experience as a senior backend engineer building complex, scalable systems in Node.js, with end-to-end ownership of architecture, data, and operations on at least one live platform.

The role is hands-on and architectural.

Expect to design system architecture, lead a small group of backend engineers, build the hardest parts yourself, set engineering standards, and partner closely with frontend, AI, and DevOps engineers.

A typical week includes an architecture decision on a new service, hands-on implementation of a critical path, a code review with mid-level engineers, and a working session with the AI engineer on an integration contract.

Responsibilities:

System Architecture

Own the backend architecture across engagements.

Make and document decisions on service boundaries, data models, API contracts, deployment topology, and trade-offs.

Hands-on Backend Delivery

Lead by example on complex modules, performance-critical paths, and high-risk areas using Node.js (Express, NestJS, Fastify) with TypeScript.

Pick up Python (FastAPI) where engagements require it.

Database Design and Performance

Drive PostgreSQL schema design, indexing, query optimisation, migrations, and capacity planning.

Set the data-modelling standard across the pod.

Caching, Queues, and Workflows

Design caching (Redis), event-driven patterns (Kafka, RabbitMQ, SQS, NATS), and long-running workflow orchestration (Temporal, BullMQ, Celery, or equivalent).

Handle retries, idempotency, and failure recovery.

Multi-Tenancy and Platform Patterns

Design and implement multi-tenant data isolation, RBAC, audit logging, and resource quotas appropriate to enterprise-grade products.

API and Integration Design

Set the standard for REST, GraphQL, and gRPC contracts.

Drive versioning, authentication (OAuth, JWT, SSO), security by default, and developer ergonomics.

Observability and Operations

Instrument services with OpenTelemetry, Prometheus, and Grafana.

Define SLOs, lead incident response, and write postmortems.

Code Quality and Mentorship

Run code reviews, define conventions, mentor mid-level engineers, and raise the engineering bar.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day.

Set the team standard for prompts, patterns, AI-assisted review, and validation of AI-generated backend code.

Client Engagement

Represent Unico Connect in technical conversations with customers.

Defend architectural decisions, communicate trade-offs, and manage scope.

Requirements:

Hands-on Production Experience as a Senior or Lead Backend Engineer in Node.js (Mandatory)

Must have personally built and shipped complex production systems in Node.js, owning architecture, data, and operations on at least one live engagement.

Full stack engineers whose deepest work is on the backend qualify.

POCs and internal tools alone do not qualify.

5+ Years of Professional Backend Engineering Experience

With at least 1 to 2 years in a senior or lead role with direct responsibility for technical decisions and team output.

Deep Node.js and TypeScript Proficiency

Strong with Express, NestJS, or Fastify.

Comfort with async patterns, streams, worker threads, and performance profiling.

Python as a Strong Plus

Hands-on production experience with FastAPI, Django, or Flask is a meaningful advantage.

Willingness and demonstrated ability to pick up Python as engagements demand is required.

PostgreSQL Depth

Schema design, normalisation, indexing, query performance, migrations, and at least one production system where you owned the data model end to end.

Caching and Event-Driven Architecture

Hands-on with Redis (or equivalent) and message queues or event-driven patterns (RabbitMQ, SQS, Kafka, NATS).

AWS Depth

Hands-on production experience with EC2, S3, RDS, IAM, VPC, ECR, and at least one of EKS, ECS, or Lambda.

Comfort owning deployment, monitoring, and cost.

System Design and End-to-End Ownership

Able to take an ambiguous problem, break it into components, evaluate alternatives, produce an architecture that holds up under review and load, plan execution, and ship with limited supervision.

AI-Assisted Engineering Experience

Daily use of Claude, Cursor, Copilot, or equivalent.

Strong discipline for reviewing and validating AI-generated backend code.

Excellent Written and Spoken English

Experience working directly with international clients.

Confident defending architectural choices in writing and in review.

Nice to Have:

• Workflow orchestration (Temporal, Airflow)
• GraphQL (Apollo, gRPC)
• Sandboxed execution environments
• Multi-tenant SaaS experience
• OpenTelemetry instrumentation
• Prior agency or consulting experience

Senior UI/UX Designer

AI Products

📍 Mumbai (On-site) | Full-time | 4-5 years

About the Role:

Unico Connect is an AI-native technology agency that builds digital products for customers across industries.

We are hiring a Senior UI/UX Designer to lead design on AI-based products.

You will shape end-to-end user experiences, build design systems, and set the visual and interaction standards across multiple products.

The role involves close collaboration with product managers, engineers, and AI specialists to translate complex workflows into clear, usable interfaces.

Responsibilities:

Own the Design Lifecycle

Own the design lifecycle for AI-based products, from research and ideation through final delivery.

Design Systems

Create and maintain design systems, component libraries, and reusable templates that scale across products.

User Research

Conduct user research, usability testing, and competitive analysis to inform design decisions.

AI Product Experience Design

Translate AI capabilities and complex workflows into intuitive interfaces that users can trust and adopt.

Cross-Functional Collaboration

Collaborate with product, engineering, and AI teams to align on scope, feasibility, and outcomes.

Stakeholder Communication

Present design work to stakeholders with clear rationale, and facilitate design reviews and critique sessions.

Mentorship

Mentor mid-level and junior designers, and help raise the design bar across the team.

Continuous Learning

Stay current with emerging patterns in AI product design, conversational interfaces, and generative UI.

Requirements:

4 to 5 Years of Experience

Four to five years of experience in UI/UX or product design, with a strong portfolio of shipped digital products.

Figma Proficiency

Proficiency in Figma, including design systems, auto-layout, variants, and prototyping.

Complex Product Design Experience

Experience designing for complex, data-heavy, or workflow-driven products.

Exposure to AI or ML-powered products is a plus.

Design Fundamentals

Strong grasp of interaction design, information architecture, and visual design fundamentals.

Design-to-Development Handoff

Working knowledge of design-to-development handoff, and comfort partnering with engineers.

Accessibility

Awareness of accessibility standards and how they influence design decisions.

Communication Skills

Excellent communication, with the ability to articulate design decisions and thought process in a clear, structured way.

Logical and Creative Thinking

Logical and creative thinking.

You can challenge a brief constructively, ask the right questions, and justify your choices with evidence.

Confidence and Collaboration

Confidence in presenting a point of view and engaging in healthy, opinionated conversations with cross-functional partners.

Problem Solving

Intellectual curiosity, attention to detail, and a genuine interest in solving ambiguous problems.

Education

Bachelor's or higher in Design, Human-Computer Interaction, Visual Communication, or a related field.

Equivalent practical experience will also be considered.

Frontend Engineer

React, TypeScript & Production Web Applications

📍 Mumbai (On-site) | Full-time | 3-5 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Frontend Engineer who will build production-grade web applications across customer engagements, partnering closely with designers, backend engineers, and AI engineers.

The mandatory requirement for this role is hands-on production experience shipping React applications, with ownership of at least one feature area end to end including state, API integration, and testing.

The role is hands-on.

Expect to implement complex flows, integrate with backend and AI services, contribute to a shared design system, write tests, and review the work of others.

A typical week includes a design handoff review, implementation of a new flow, a code review session, and a working call with a backend engineer on API contracts.

Responsibilities:

Production UI Development

Build production-grade React UI for customer engagements, including complex forms, dashboards, data-dense views, and AI-driven interactions.

API Integration

Integrate with REST and GraphQL APIs.

Handle authentication, streaming responses (Server-Sent Events, WebSockets), retries, and graceful error states.

State Management

Build state architecture using Redux, Zustand, Jotai, or equivalent.

Handle async state, optimistic updates, and cross-component coordination.

Design System Contribution

Implement components within an established design system.

Maintain token discipline and contribute back to shared components.

Testing

Write unit, integration, and end-to-end tests using Jest, React Testing Library, and Playwright or Cypress.

Performance and Accessibility

Profile and optimise rendering and bundle size.

Apply WCAG 2.1 AA practices in everyday work.

AI-Assisted Development

Use Claude, Cursor, and similar tools day to day.

Build discipline for reviewing and validating AI-generated code.

Requirements:

Hands-on Production React Experience (Mandatory)

Must have personally shipped at least one feature area end to end in a production React application, owning state, API integration, and testing.

POCs and internal tools alone do not qualify.

3 to 5 Years of Professional Frontend Engineering Experience

Strong JavaScript, TypeScript, and React

Solid with hooks, context, and modern patterns.

Working comfort with Next.js (SSR, SSG, app router).

State Management

Production experience with Redux, Zustand, Jotai, or equivalent.

CSS and Styling

Strong with Tailwind, CSS Modules, or CSS-in-JS.

Comfortable building responsive layouts.

REST and GraphQL

Comfortable consuming both.

Working knowledge of streaming responses and async patterns.

Testing Fluency

Jest, React Testing Library, and at least one of Playwright or Cypress.

Git and CI/CD Basics

Comfortable with feature branching, pull requests, and CI-integrated test runs.

Strong Written and Spoken English Communication

Nice to Have:

• Experience with editor or canvas UIs
• Storybook
• Animation libraries (Framer Motion, GSAP)
• Exposure to AI-driven UI patterns
• Visual regression testing tools

Tech Lead

Full Stack, Architecture & Client Delivery

📍 Mumbai (On-site) | Full-time | 5-6 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Tech Lead who will own the technical direction of full stack engagements, lead a small pod of engineers, and represent Unico Connect directly in front of customers.

The mandatory requirement for this role is hands-on production experience as a senior or lead engineer building full stack web applications with React on the frontend and either Node.js or Python on the backend.

The role is hands-on.

Expect to spend meaningful time on architecture, complex implementation, and code reviews, while also driving delivery, mentoring a pod of 3 to 6 engineers, running client conversations, and contributing to solutioning on new opportunities.

A typical week includes a design review on a new module, a working session with a client product owner, paired implementation on a complex flow, and pre-sales input on an active opportunity.

Responsibilities:

Solutioning and Architecture

Own end-to-end architecture for client engagements: system design, API contracts, data models, integrations, deployment topology, and trade-off analysis.

Document and defend decisions in writing and in client reviews.

Hands-on Full Stack Delivery

Lead by example on complex modules, performance-critical paths, and high-risk areas of the system using React (with Next.js where relevant) and Node.js (Express, NestJS) or Python (FastAPI, Django, Flask).

Database Design and Performance

Drive PostgreSQL schema design, indexing strategy, query optimisation, migrations, and capacity planning.

Set the standard for data modelling across the pod.

Cloud and Infrastructure

Set up and operate production workloads on AWS, GCP, or Azure.

Make and own decisions on compute, storage, networking, CI/CD pipelines, observability, and cost.

Code Quality and Engineering Standards

Run code reviews, define engineering conventions, and raise the quality bar across the team.

Set the standard for testing, linting, branching, release management, and incident response.

Team Leadership and Mentorship

Lead, mentor, and grow a pod of 3 to 6 engineers.

Plan sprints, unblock the team, run retros, and own delivery commitments.

Client Engagement

Act as the primary technical point of contact for the client.

Run technical discussions, present trade-offs, manage scope and risks, and keep stakeholders informed in writing.

Pre-Sales and Solutioning

Partner with sales and account leadership on new opportunities, including discovery calls, effort estimation, architecture diagrams, and solution write-ups.

AI-Assisted Development

Use Claude, Cursor, and similar tools day to day.

Set the standard for the team on prompts, patterns, AI-assisted code review, and where these tools are and are not appropriate.

AI Feature Delivery

Where an engagement calls for it, design and ship LLM-based features into production, including prompt design, retrieval pipelines, evaluation, observability, and guardrails.

Requirements:

Hands-on Full Stack Production Experience as a Senior or Lead Engineer (Mandatory)

Must have personally built and shipped production web applications using React on the frontend and either Node.js or Python on the backend.

POCs, internal tools, and coursework do not qualify.

5 to 6 Years of Professional Software Engineering Experience

Including at least 1 to 2 years in a tech lead, team lead, or senior engineering role with direct responsibility for technical decisions and team output.

Hands-on Cloud Experience on at Least One of AWS, GCP, or Azure

Including deploying and operating production workloads.

Comfort with at least three of: EC2 or equivalent compute, S3 or equivalent object storage, Lambda or serverless functions, RDS or managed databases, CloudFront or equivalent CDN, IAM, VPC.

Strong Proficiency in JavaScript and TypeScript

With React and Next.js (SSR, SSG, app router) on the frontend, and either Node.js (Express, NestJS) or Python (FastAPI, Django, Flask) on the backend.

API design experience across REST and GraphQL.

Willingness and demonstrated ability to pick up the other backend stack as engagements demand.

Production Experience with Docker, Git-Based Workflows, and CI/CD Pipelines

(GitHub Actions, GitLab CI, CircleCI, or equivalent).

Strong PostgreSQL Skills

Schema design, normalisation, indexing, query performance, migrations, and at least one production system where you owned the data model end-to-end.

Caching and Event-Driven Architecture

Hands-on with Redis (or equivalent) for caching and session management, and message queues or event-driven patterns (RabbitMQ, SQS, Kafka, or NATS) for asynchronous workflows.

AI and LLM Feature Delivery in Production

Experience designing and shipping at least one AI feature to production, covering prompt design, retrieval-augmented generation (RAG), embeddings, evaluation, observability, and guardrails.

POCs and demos do not qualify.

System Design Depth and End-to-End Ownership

Able to take an ambiguous problem, break it into components, evaluate alternatives, produce an architecture that holds up under review and load, plan execution, and ship to production with limited supervision.

Excellent Written and Spoken English

Experience working directly with international clients.

Confident, clear, and firm in stakeholder communication.

Comfortable presenting to senior stakeholders, pushing back where needed, and managing expectations across time zones.

DevOps Engineer

AWS Infrastructure, CI/CD & Production Operations

Mumbai (On-site) | Full-time | 2-4 years

About the role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a DevOps Engineer who will own day-to-day cloud infrastructure, deployment automation, and production operations across active customer engagements.

The mandatory requirement for this role is hands-on production experience on AWS, with infrastructure as code, container orchestration, and CI/CD pipelines owned end to end on at least one live customer workload. The role is hands-on. Expect to operate Kubernetes clusters, build CI/CD pipelines, automate environment provisioning, manage TLS and DNS, set up observability, and partner with backend and AI engineers to ship reliably. A typical week includes a Terraform refactor, a deployment pipeline build for a new service, an incident response on a production cluster, and a cost review.

Responsibilities:

• AWS infrastructure: Design and operate production infrastructure on AWS using EC2, EKS or ECS, S3, RDS, IAM, VPC, CloudFront, and Route53. Own configuration, networking, and cost.
• Infrastructure as code: Write and maintain Terraform or Pulumi modules. Drive consistency across environments and tenants through IaC rather than manual configuration.
• Kubernetes and containers: Operate production EKS clusters. Manage Helm charts, Ingress, autoscaling, secrets, and workload isolation.
• CI/CD pipelines: Build and maintain pipelines using GitHub Actions, GitLab CI, or equivalent. Include automated tests, security scans, and rollback paths.
• TLS, DNS, and CDN automation: Automate domain provisioning, TLS issuance (Let's Encrypt, cert-manager, ACM), and CDN configuration (CloudFront, Cloudflare).
• Observability and incident response: Set up monitoring, logging, and alerting using Prometheus, Grafana, ELK, Loki, or CloudWatch. Lead incident response and write postmortems.
• Secrets and security: Manage secrets through Vault, AWS Secrets Manager, or KMS. Apply least-privilege IAM and review access regularly.
• Cost monitoring: Track and optimise AWS spend across environments. Surface waste and propose remediations.
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Requirements:

• Hands-on AWS production experience (mandatory). Must have personally operated production workloads on AWS, with responsibility for IaC, deployments, and incident response on at least one live customer or internal-platform deployment. POCs and lab environments do not qualify.
• 2 to 4 years of hands-on DevOps or infrastructure experience. Candidates with slightly less experience but strong demonstrated ownership are welcome to apply.
• AWS depth. Hands-on with EC2, S3, IAM, VPC, EKS or ECS, RDS, CloudFront, and Route53. Working knowledge of CloudWatch and AWS cost tooling.
• Kubernetes in production. Hands-on operation of EKS or equivalent. Comfort with Helm, Ingress controllers, autoscaling, and resource quotas.
• Infrastructure as code. Strong with Terraform (preferred) or Pulumi. Modular code, state management, and review discipline.
• CI/CD pipelines. Production experience with GitHub Actions, GitLab CI, or equivalent. Comfort with multi-environment pipelines and release strategies.
• Scripting and automation. Strong Bash and Python (or Go) for tooling. Linux fluency at the command line.
• Observability stack. Hands-on with Prometheus, Grafana, ELK or Loki, and at least one APM tool (Datadog, New Relic, or equivalent).
• Networking, TLS, and security fundamentals. Comfortable with DNS, TLS certificate lifecycle, VPC peering, and security groups.



Nice to have: multi-tenant SaaS infrastructure experience; service mesh (Istio, Linkerd); GitOps (ArgoCD, Flux); sandboxed execution environments (Firecracker, gVisor); exposure to platform engineering or developer-platform teams.

Senior Xano Developer

Visual Backend Development, APIs & AI-Assisted Build

📍 Mumbai (On-site) | Full-time | 3-5 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Xano Developer who will build backend systems and APIs for our customer engagements on Xano, the visual backend development platform.

The mandatory requirement for this role is hands-on production backend engineering experience, including PostgreSQL data modelling and REST API design, in either a Node.js or Python environment.

Prior production work on Xano is strongly preferred.

The role is hands-on and customer-facing. You will own backend delivery across engagements: designing data models, building API flows in Xano, integrating third-party services, and partnering with frontend, mobile, and AI engineers on contracts and behaviour.

The work spans all three Xano build modes: no-code function stacks, custom code through Xano’s scripting and code blocks, and Xano’s AI assistance and agentic features.

A typical week includes a data model review for a new engagement, building a complex API flow in Xano, integrating a third-party webhook, and a customer working session on a new module.

Responsibilities:

Backend Delivery on Xano

Own end-to-end backend implementation on Xano: database schema, API endpoints, function stacks, background tasks, and integrations.

Ship production-ready work that meets customer requirements and engineering quality standards.

Build Across All Three Xano Modes

Use Xano’s no-code function stacks for standard CRUD and business logic.

Drop into custom code (JavaScript, Python through code blocks, expressions) where visual flows would be unwieldy.

Use Xano’s AI assistance and agentic features to accelerate routine build work.

Database Design on PostgreSQL

Own data model decisions for each engagement: table design, relationships, indexes, addons, and query performance.

Make schema choices that hold up as product usage grows and that map cleanly to the API contracts the client needs.

API Design and Integration

Design clean REST API contracts that the frontend, mobile, and third-party consumers can rely on.

Cover authentication, input validation, pagination, error handling, and rate limiting.

Integrate external services (payment gateways, messaging, storage, AI providers) through Xano’s connectors and custom requests.

Product Thinking and Solutioning

Translate fuzzy product asks from customers into concrete backend solutions.

Ask the right questions about edge cases, data lifecycle, multi-tenancy, and access control before building.

Push back on requirements that will cause pain later.

Customer Communication

Work directly with customers in discovery, design reviews, demos, and weekly working sessions.

Explain trade-offs in plain language, present options with clear recommendations, and write tight technical updates.

AI-Assisted Backend Development

Use Xano’s built-in AI features as well as external AI tools (Claude, Cursor, and similar) day to day for schema drafts, function stack scaffolding, query writing, integration setup, and review.

Develop strong instincts for when AI output is usable as-is and when it must be reworked.

Quality, Testing, and Reliability

Test the flows you ship.

Set up sensible error handling, logging, and alerts for the backend services you own.

Participate in incident response when something breaks in production.

Documentation and Handover

Document data models, API contracts, and non-obvious decisions inside Xano and in shared docs so the rest of the team and the customer can pick up the work without you in the room.

Continuous Learning

Track changes to the Xano platform, including new features, performance improvements, and AI capabilities.

Apply them to active engagements where they reduce build effort or improve product outcomes.

Requirements:

Hands-on Production Backend Engineering Experience (Mandatory)

Must have personally shipped backend systems to production for real users, with ownership of API design and data modelling.

POCs, coursework, and internal-only tools do not qualify.

3 to 5 Years of Professional Backend Engineering Experience

In either a Node.js or Python environment.

Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

Strong PostgreSQL Skills

Schema design, indexing, query writing, and migrations on at least one production system.

Able to reason about query performance and design data models that hold up under realistic product usage.

REST API Design and Integration Depth

Comfort designing API contracts that are clean, predictable, and easy for frontend, mobile, and third-party consumers to work with.

Experience integrating external services such as payment gateways, messaging providers, storage, and AI APIs.

Familiarity with at Least One Node.js or Python Backend Stack

Such as Express, NestJS, Fastify, FastAPI, Django, or Flask.

Comfort reading and writing application code outside of visual environments when the situation calls for it.

Product Thinking and Solutioning

Ability to take a fuzzy product brief, ask the right questions, and propose a backend design that is fit for purpose.

Strong instincts for what to build first, what to defer, and what not to build.

Strong Written and Spoken English Communication

Confident in customer working sessions and design reviews.

Comfortable writing precise technical documentation and explaining trade-offs to non-engineering stakeholders.

Cloud and Deployment Fundamentals

Working knowledge of at least one of AWS, GCP, or Azure: deploying services, reading logs, managing environments, and basic operational tasks.

Familiarity with Docker is a plus.

Bachelor’s Degree

Bachelor’s degree in Computer Science, Information Technology, or a related engineering discipline.

Exceptional candidates with demonstrable production experience and strong portfolios may be considered without a formal degree.

Nice to Have

• Prior production experience on Xano, Bubble, Retool, or comparable visual or low-code backend platforms
• Full stack experience with React, Next.js, React Native, or Flutter
• Experience integrating LLM APIs (OpenAI, Anthropic, Google) into backend workflows
• Multi-tenant SaaS product experience
• Prior agency, consulting, or product-engineering experience

Full Stack Support Engineer

Node.js, React & Production Application Support

📍 Remote | Full-time | Night Shift | 3+ Years

About the Role

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Full Stack Support Engineer who will own day-to-day application support for a live customer product built on Node.js and React, working a fixed night shift aligned to North American business hours.

The mandatory requirements for this role are prior professional experience working a night shift, and the willingness to continue working a permanent night shift, Monday through Friday, approximately 7:00 PM to 4:30 AM IST, with on-call support coverage on weekends.

The role is fully remote.

The work is hands-on across the stack: triaging issues from monitoring alerts and customer tickets, performing root cause analysis, shipping bug fixes, applying minor framework and library updates, and communicating with the customer directly during the shift.

When there is no active support work, the engineer will contribute to other development projects within the company, so consistent productive output across the shift is expected.

Responsibilities:

Incident Response and SLA Adherence

Acknowledge and act on alerts and customer-raised tickets within the SLA window.

Critical incidents require response within 1 hour and best-effort resolution within 2 to 4 hours.

P1 issues require response within 2 to 4 hours and resolution within 1 business day.

P2 and P3 issues follow the documented SLA matrix.

Bug Fixes and Production Support

Investigate and resolve defects in previously built functionality across the customer-facing portal, internal portal, backend services, and third-party integrations.

Write clean fixes with appropriate tests and documentation.

Monitoring and Proactive Triage

Operate the application and infrastructure monitoring stack.

Investigate anomalies before they become incidents.

Tune alerts to reduce noise and improve signal.

Customer Communication During the Shift

Communicate directly with the customer in English during incidents and routine support, in writing and on calls.

Set clear expectations on status, root cause, and timeline.

Close the loop after resolution.

Minor Framework and Dependency Updates

Apply minor version upgrades to operating systems, frameworks, and libraries to maintain compatibility and security.

Test rigorously before promoting to production.

Hands-On Development Across the Stack

Work in the existing Node.js (Express, NestJS) backend and React frontend codebase.

Make focused changes that respect the existing architecture and patterns.

Contribution to Other Development Projects

When the support workload is light, contribute to other active development projects within Unico Connect.

Pick up well-scoped tasks, ship them to the team’s quality standard, and remain available to drop back into support work as soon as it is needed.

Root Cause Analysis and Write-Ups

For every meaningful incident, document the cause, the fix, the customer impact, and any follow-up actions to prevent recurrence.

Weekend On-Call Coverage

Provide on-call support coverage on weekends.

Respond to alerts and customer tickets within the defined SLA window.

AI-Assisted Support Workflows

Use Claude, Cursor, and similar tools day to day for triage, log analysis, code reading, and patch drafting.

Apply judgment on when to trust AI-generated output and when to verify.

Handover Discipline

Maintain clean shift handover notes for the day-shift team.

Track open issues, in-progress investigations, and customer commitments so nothing drops between shifts.

Requirements:

Prior Professional Night-Shift Experience (Mandatory)

Candidates must have worked a permanent night shift in a prior professional role for a meaningful period of time.

Adjacent late-evening shifts or occasional on-call do not qualify.

Willingness to Work a Permanent Night Shift Aligned to North American Business Hours, with On-Call Support Coverage on Weekends (Mandatory)

The shift is Monday to Friday, approximately 7:00 PM to 4:30 AM IST.

Candidates who cannot commit to night-shift hours on an ongoing basis should not apply.

3+ Years of Professional Full Stack Engineering Experience

With hands-on production work in both Node.js and React.

Strong JavaScript and TypeScript Proficiency

With React on the frontend and Node.js (Express, NestJS) on the backend.

API design experience with REST.

Comfortable reading and modifying an existing production codebase without breaking adjacent functionality.

Production Debugging and Incident Response Instincts

Ability to read logs, traces, and metrics to isolate a problem quickly.

Comfort triaging across application code, database queries, third-party API failures, and infrastructure.

Working Experience with Relational Databases

(PostgreSQL or MySQL), including reading and writing SQL, basic schema understanding, and the ability to investigate data-related incidents.

Familiarity with Cloud Infrastructure

On AWS, GCP, or Azure, at the level of reading logs, restarting services, deploying through CI/CD pipelines, and basic operational tasks.

Working Knowledge of Git, CI/CD Pipelines, and Monitoring Tools

At least one monitoring or observability tool (Datadog, New Relic, Sentry, CloudWatch, Grafana, or equivalent).

Strong Written and Spoken English Communication

This role involves direct customer interaction during the shift.

Calm, clear, professional communication in writing and on calls is non-negotiable.

Bachelor’s Degree

Bachelor’s degree in Computer Science, Information Technology, or a related engineering discipline.

Exceptional candidates with demonstrable production experience and strong portfolios may be considered without a formal degree.

Alertness, Judgment, and Ownership Mindset

Night-shift support work demands self-direction, attention to detail under low-supervision conditions, and the discipline to follow process when fatigued.

Nice to Have

• Prior experience in application support, AMC, or managed services engagements
• On-call experience with documented SLAs
• Experience with feature flag tools, error tracking platforms, or APM dashboards
• Exposure to AI-assisted development tools in a support context

Senior AI Engineer

Code Generation, Agent Architecture & LLM Systems

📍 Mumbai (On-site) | Full-time | 5+ years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.

The mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.

The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.

You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent Architecture

Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.

Make and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.

Code Generation Pipeline

Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.

Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies.

Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-Repair Loop

Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.

This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context Management

Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.

Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.

Own token budgeting and prompt caching strategy.

Prompt Engineering as a Discipline

Own the system prompt and per-task prompt variants (new feature, bug fix, styling change).

Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.

Version prompts like code with changelogs and rollback capability.

Evaluation and Quality Measurement

Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.

Define regression gates that block quality-degrading changes from shipping.

Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.

This responsibility is non-negotiable at this level.

Model Strategy and Cost

Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation.

Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.

Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and Reliability of Agent Behaviour

Defend against prompt injection from user content and fetched web content.

Ensure secrets never appear in generated client code.

Define what the agent's tools may and may not do in collaboration with the platform team.

Contribute to output moderation and abuse-pattern awareness.

Mentorship and Engineering Standards

Run code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.

Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)

Must have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.

POCs, internal demos, and tutorial-grade work do not qualify.

5+ Years of Professional Software or AI Engineering Experience

With at least 3 years focused on LLM applications, AI engineering, or production AI systems.

Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python Proficiency and Service Development

Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.

Not notebook-only.

Depth Across LLM APIs and Agent Systems

Production experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).

Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, Systematic Evaluation Practice - Non-Negotiable

Must have built evaluation harnesses that gate production releases, not ad-hoc testing.

Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.

Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost Discipline for Production AI

Track record of measurable cost optimisation on production AI features.

Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS Working Knowledge

Hands-on with EC2, S3, IAM, and Docker.

Comfort with CI/CD workflows and deploying AI services.

Awareness of LLM Security Failure Modes

Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to Have

• Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work
• MCP server authoring
• Open-source AI contributions
• Published technical writing on LLM systems
• Multi-modal model experience
• Fine-tuning exposure (LoRA, QLoRA, PEFT)

Senior MLOps Engineer

LLM Operations, Observability & Eval Infrastructure

📍 Mumbai (On-site) | Full-time | 5-7 years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior MLOps Engineer for a dedicated client engagement focused on building an AI-powered application builder platform. The platform consumes LLMs at scale through provider APIs.

This role owns the operational discipline around production LLM consumption - increasingly called LLMOps - covering observability, evaluation infrastructure, model lifecycle, cost operations, prompt deployment, and agent run reliability.

The mandatory requirement is hands-on production experience operating LLM-backed systems, with a strong DevOps or SRE foundation. This is not a model training or ML science role.

The work is making the system around the AI engineer's designs observable, controlled, reliable, and economically accountable. You will pair daily with the Senior AI Engineer, who designs prompts, evals, and agent behaviour - you operationalise those systems for production.

A typical week includes a tracing audit on a degraded agent run, an eval pipeline build for a new model release, a cost attribution review, and a staged prompt rollout.

Responsibilities:

Observability and Tracing

Build and own end-to-end tracing for agent runs: every prompt, response, tool call, token count, latency, and cost, linked to user session and project.

Stand up and operate LLM observability tooling (Langfuse, LangSmith, Braintrust, or Arize Phoenix).

Make debugging a single bad agent run among thousands a routine workflow through searchable traces, failure taxonomies, and dashboards segmented by task type.

Evaluation Infrastructure as a Production System

Operationalise the eval suite designed by the Senior AI Engineer: automated execution in CI on every prompt or model change, with results stored and trended over time.

Implement regression gates that block quality-degrading changes from shipping.

Build production sampling to continuously score a sample of real agent runs and catch quality drift that offline evals miss.

Model Lifecycle Management

Pin model versions, never "latest".

Own the upgrade process: run the eval suite against new model releases and manage eval-gated migrations.

Maintain fallback chains across providers for graceful degradation or queueing during outages.

Track provider deprecation schedules and plan migrations ahead of forced cutoffs.

Cost Operations

Implement per-user and per-task cost attribution - token spend is the platform's largest variable cost and requires the same rigour as cloud cost management.

Set up budget alerts and anomaly detection so a single user or bug cannot burn significant spend overnight.

Monitor prompt cache hit rates and quantify savings.

Manage capacity planning around provider rate limits, including quota negotiation and throughput tiering.

Prompt and Configuration Deployment

Treat prompts as production artifacts: version control for prompts and agent configurations, staged rollout infrastructure (deploy a prompt change to a percentage of traffic before full rollout), A/B testing infrastructure, instant rollback, and audit history covering which prompt version served which user and when.

Reliability Engineering for Agent Runs

Agent runs are long, stateful, and failure-prone.

Own retry and resume semantics so a run that fails mid-way does not restart from scratch.

Implement timeouts and circuit breakers on provider calls, dead-letter handling for failed runs, and queue and concurrency management for agent workloads.

SLO Ownership and Incident Response

Define and track SLOs for agent run latency and completion rates.

Lead incident response when SLOs are breached.

Write postmortems.

Surface reliability risks proactively before they reach users.

Safety and Compliance Operations

Run the moderation pipeline (prompt and output classification) in production.

Monitor for abuse patterns and own incident response when the agent misbehaves at scale.

Maintain audit logs and implement data retention and residency policies for prompts and generated code as enterprise requirements emerge.

AI-Assisted Engineering Discipline

Use Claude, Cursor, and similar tools day to day for infrastructure code, scripts, and pipelines.

Set the team standard for safe use, review, and validation of AI-generated infrastructure before it ships.

Requirements:

Hands-on production ownership of LLM-backed systems in operation (mandatory).

Must have personally shipped and operated at least one LLM-powered system in production, with operational responsibility including oncall, incident response, and reliability ownership.

Alternatively: strong DevOps or SRE background with demonstrated hands-on familiarity with LLMOps tooling (Langfuse, LangSmith, Braintrust, Arize, or equivalent).

POCs and lab work do not qualify.

5+ years of overall engineering experience

With at least 2 years in DevOps, SRE, platform engineering, or LLM operations roles.

This is not an ML science role.

A DevOps or SRE background with a substantive pivot into LLMOps is a strong qualification.

Observability and Tracing Depth

Production experience with LLM observability tooling - Langfuse, LangSmith, Braintrust, or Arize Phoenix.

Comfortable instrumenting with OpenTelemetry, Prometheus, and Grafana.

Able to build and search trace pipelines, define failure taxonomies, and surface quality signals from production traffic.

CI/CD and Quality Gate Experience

Strong with GitHub Actions or GitLab CI.

Experience building automated quality gates: eval-gated pipelines, regression enforcement, or coverage gates that block degrading changes from shipping.

Cost Management and Attribution for Usage-Based Services

Experience owning cost attribution for cloud API spend or equivalent.

Comfortable with budget alerts, anomaly detection, and per-user or per-task cost breakdowns.

Reliability Engineering for Long-Running, Stateful Workloads

Experience with queues, retry patterns, idempotency, and failure recovery on asynchronous or multi-step workloads.

Comfortable defining SLOs and being accountable for them on production systems.

Multi-Provider API Management

Familiarity with LLM provider rate limits, version pinning, fallback chains, and quota management across OpenAI, Anthropic, Google, or equivalent.

Infrastructure as Code and Deployment Automation

Hands-on with Terraform or Pulumi and Docker.

AWS working knowledge (EC2, S3, IAM, EKS or ECS).

Strong with CI/CD for deploying services and configuration changes safely.

Nice to Have

• Experience with prompt A/B testing or staged rollout infrastructure
• Workflow orchestration (BullMQ, Temporal, Celery)
• Content moderation pipeline experience
• Data residency and compliance requirements for AI systems
• Kubernetes (EKS) in production
• AWS certifications

About the Role

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies. We are hiring a Backend Engineer for a dedicated client engagement building an AI-powered application builder platform.

The backend is the operational core of the product: it manages user projects and sessions, coordinates long-running AI agent workloads, maintains project state, and serves as the integration layer between the frontend, the AI system, and the underlying infrastructure.

The mandatory requirement is hands-on production experience shipping Node.js services, with end-to-end ownership of API design, data modelling, and at least one production system involving background job processing or event-driven patterns.

Responsibilities

API and service development: Design and build REST APIs in Node.js with TypeScript. Cover authentication, session management, input validation, structured error handling, streaming responses (SSE, WebSockets), and rate limiting. Maintain clean API contracts that the frontend and AI system can rely on.

Database design and management: Own PostgreSQL schema design for product domains including user accounts, projects, file trees, session state, and generated artefacts. Write efficient queries, manage migrations, and optimise for read patterns that serve a real-time editor experience.

Caching strategy: Implement and maintain caching with Redis for session data, project state, and frequently read configuration. Design cache invalidation logic that keeps the editor experience consistent without stale reads.

Queue and background job management: Implement and operate background job infrastructure using BullMQ or equivalent. AI agent runs are long-running and stateful; handle retries, failure states, priority queues, and concurrency limits.

AI system integration: Build the integration layer between the backend and the AI agent system. Manage job dispatch, result handling, streaming output to the frontend, and error propagation.

Multi-tenancy and access control: Implement tenant data isolation, RBAC, and resource ownership enforcement across all API surfaces.

Observability and reliability: Instrument services with structured logging, metrics, and tracing. Write defensive code with sensible timeouts, fallback behaviour, and circuit breaking on external dependencies.

Testing and code quality: Write unit and integration tests for the services you ship. Review the work of peers and contribute to shared engineering conventions.

Requirements

• Hands-on production Node.js experience (mandatory) — must have personally shipped at least one feature area end to end in a production Node.js service, owning API design, data modelling, and testing.

• 3 to 5 years of professional backend engineering experience. Candidates with slightly less time but strong demonstrated ownership are welcome to apply.

• Strong Node.js and TypeScript. Production experience with Express, NestJS, or Fastify. Solid with async patterns, streaming, error handling, and building services that run reliably under sustained load.

• PostgreSQL depth. Schema design, query writing, indexing, and migrations on at least one production system.

• Redis and caching. Production experience using Redis for caching and session management. Understands cache invalidation trade-offs.

• Queue and background job systems. Hands-on with BullMQ, RabbitMQ, SQS, or equivalent. Experience managing retries, dead-letter queues, job priority, and concurrency control.

• AWS working knowledge. Comfortable with EC2, S3, RDS, SQS, and IAM. Familiar with Docker and basic deployment and environment management.

• Strong written and spoken English. Able to communicate clearly with engineers across disciplines and write precise technical documentation.

Nice to Have

Experience integrating with AI or LLM services (streaming responses, structured outputs, retry patterns); WebSocket or SSE implementation for real-time features; multi-tenant SaaS product experience; GraphQL; OpenTelemetry instrumentation; prior work on developer tools or editor-style products.