HyrHub

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.
• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.
• Only immediate joiners are considered.

Immediate Joiner - 15 days Notice period

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.

• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.

Key Skills :

• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through

to React-based user interfaces, deployed on Databricks

• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including

decision capture, audit logging and file exports for downstream systems

• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work

alongside ML models

• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited

outputs

• Writes performant SQL against governed data and ensures services operate within defined access

boundaries

• Builds interactive screens, dashboards and conversational interfaces that let users review and act

on AI recommendations

• Works closely with GenAI/ML engineers, data engineers and BA

Only immediate joiners are considered.

Key Skills:

Python & System Design: Strong expertise in Python and system design, with proven experience architecting scalable, production-grade systems.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Cloud & Data Architecture: Deep understanding of data and cloud architecture across AWS and Azure, including multi-store data design, distributed systems, streaming, security, and cost optimization.

Azure Databricks: Hands-on production experience with Azure Databricks architecture, including Unity Catalog, Delta Lake, cluster policy design, job orchestration, and Terraform provisioning.

Supply Chain & Inventory Management: Strong domain knowledge of supply chain and inventory operations, including demand planning, MRP logic, inventory parameters, and translating business planning decisions into data requirements.

System Architecture & Technical Decision-Making: Ability to make sound architectural decisions based on first principles, evaluate technical trade-offs, and avoid unnecessary complexity and abstraction.

LLM & Agentic AI: Proven experience building LLM-based and agentic systems from the ground up and evaluating them based on reproducibility, calibration, and cost.

Technical Leadership: Ability to influence teams without direct authority, establish technical standards, prepare technical specifications and documentation, and mentor team members.

Experience in pharmaceutical or regulated industries is highly valued.

• Decompose legacy monoliths into agent‑readable, modular systems with strict boundaries and single responsibility
• Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contract‑driven interfaces
• Enforce SOLID principles, Dependency Injection, and Hexagonal Architecture to ensure deterministic AI execution and low regression risk
• Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AI‑driven engineering workflows
• Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AI‑consumable tools
• Own contract‑first API design as the primary interface between human intent and autonomous agent execution
• Act as architectural gatekeeper for AI‑generated pull requests, ensuring scalability, security, and long‑term maintainability
• Mandate test‑driven development (TDD) and characterization testing to preserve legacy behavior during refactoring
• Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity

Requirement:

• 15+ years in software architecture, platform engineering, or technical leadership
• Proven experience modernizing large, undocumented legacy systems
• Deep hands‑on expertise with TypeScript, .NET, and Node.js
• Strong background in API design, distributed systems, and modular architectures
• Practical experience with agentic development, MCP, LLM tooling, or AI‑assisted engineering

Required Skills:

• Strong proficiency in C++, with fair knowledge of the language specification.  
• Should have good knowledge of the standard library STL containers, multi-threading concepts and algorithms.
• Good understanding of memory management. Must be familiar with templating in C++
• Knowledge of the latest C++ 17 or above will be an added advantage. 
• Knowledge of writing modules for high-level languages such as Node.js, Python, etc. will be appreciated
• Should have strong Linux development and debugging skills − Candidates with knowledge of Financial domain like equity and trading domain would be an added advantage.
• Mandatory Skills: C++, STL, Multithreading, Socket Programming, LINUX, Memory Management, System Design, Design Patterns, Design & Deployment.

Note: Only Immediate joiners are considered

Key Skills:

• Builds AI-powered business applications end to end, from the Python/FastAPI service layer through to React-based user interfaces, deployed on Databricks
• Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including decision capture, audit logging and file exports for downstream systems
• Codes rule-based decision engines in Python (e.g. allocation or replenishment logic) that work alongside ML models
• Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited outputs
• Writes performant SQL against governed data and ensures services operate within defined access boundaries
• Builds interactive screens, dashboards and conversational interfaces that let users review and act on AI recommendations
• Works closely with GenAI/ML engineers, data engineers and BA

Primary tech stack:

Python, Fast API, REST API design, SQL, Databricks Apps, Databricks SQL, Unity Catalog, LLM agent integration, React, TypeScript, Git / CI-CD

Secondary tech stack:

Pydantic, Async Python, Pytest, MLflow, Delta Lake, State management, Figma-to-code

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered, 

As an Engineering Manager, you'll lead efforts to strengthen and optimize our state-of-the-art systems, ensuring high performance, scalability, and efficiency across our suite of trading solutions.

The core responsibilities for the job include the following:

Technical Expertise:

• C++ coding and debugging to strengthen and optimize systems.
• Design and architecture (HLD/LLD) to ensure scalable and robust solutions.
• Implementing and enhancing DevOps, Agile, and CI/CD pipelines to improve development workflows.
• Managing escalations and ensuring high-quality customer outcomes.

Architecture and Design:

• Define and refine the architectural vision and technical roadmap for enterprise software solutions.
• Design scalable, maintainable, and secure systems in line with business goals.
• Collaborate with stakeholders to translate requirements into technical solutions.
• Driving engineering initiatives to foster innovation, efficiency, and excellence.

Project Management:

• Oversee project timelines, deliverables, and quality assurance processes.
• Coordinate cross-functional teams to ensure seamless integration of systems.
• Identify risks and proactively implement mitigation strategies.

Technical Leadership:

• Lead and mentor a team of engineers, fostering a collaborative and high-performance culture.
• Provide technical direction and guidance on complex software engineering challenges.
• Drive code quality, best practices, and standards across the engineering team.

Requirements:

• 6-13 years in the tech industry, with 2-4 years in technical leadership or managerial roles.
• Technical Expertise: Expertise in C++ development, enterprise architecture, and scalable system design, and proficiency in performance optimization, scalability, software architecture, and networking principles.
• Extensive experience managing the full development lifecycle of large-scale software products, from concept to deployment.
• Strong knowledge of STL containers, multi-threading concepts, and algorithms.
• Solid understanding of memory management and efficient resource utilization.
• Microservices Architecture Expertise: Experience in designing and implementing scalable, reliable microservices.
• Strong Communication and Decision-making skills: Ability to clearly articulate trade-offs, make informed decisions, and ensure alignment across stakeholders.
• Commitment to Creating and fostering Engineering Excellence: Deep understanding of best practices, including code quality, testability, security, and release management, and passion for fostering a strong engineering culture and continuously improving developer workflows and tools.
• Self-Driven and Motivated: Ability to operate independently while driving impactful results.

Experience and Expertise

• 2+ years of experience in C++ application development.
• Hands-on experience with C++11 or above.
• Strong knowledge of object-oriented programming and software design.
• Deep understanding of STL, multi-threading, socket programming, and data structures.
• Solid grasp of Linux development and debugging techniques.
• Proficient in using GCC, GDB, and Makefile.
• Familiarity with Valgrind and similar analysis tools.
• Experience with version control tools like Git.
• Experience writing and maintaining automated tests.
• Experience in capital markets/trading domain is a plus.