CLOUDSUFI

About Us:

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Our Values

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

About the role

CloudSufi is hiring an AgentOps Engineer to own the runtime, infrastructure, and operational monitoring for an AI agent testing platform deployed for an enterprise client. You will deploy and instrument agents for testing, set up observability and continuous evaluation on live traffic, and manage the cloud infrastructure the platform runs on.

Responsibilities:

- Deploy and instrument AI agents for testing and monitoring.

- Set up observability — traces, logs, and metrics — and continuous evaluation on production traffic.

- Build drift detection and alerting so quality regressions are caught early.

- Own the cloud infrastructure and CI/CD automation supporting the platform.

- Manage environments, access, and operational reliability.

Required qualifications:

- 5+ years in DevOps, MLOps, or platform engineering.

- Strong Google Cloud experience (Cloud Run, Cloud Build, Pub/Sub, Cloud Logging and Monitoring, IAM) or equivalent cloud platform.

- Experience with CI/CD automation and infrastructure as code.

- Familiarity with deploying LLM or AI agent workloads.

Preferred qualifications:

- Experience with OpenTelemetry and AI/agent observability.

- Exposure to Vertex AI, Gemini Enterprise Agent Platform, or ADK.

About Us:

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Our Values:

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement:

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

Role Summary

We are seeking a forward-thinking, strategic PMO Leader to organize and energize our enterprise project portfolio. This role focuses on scaling delivery and driving Agile/hybrid transformation. The ideal candidate will modernize our PMO by leveraging AI tools and automation to re-engineer legacy workflows, optimize resource utilization, and accelerate project delivery.

Key Responsibilities

• Portfolio Governance: Define, implement, and maintain standardized PMO processes, policies, and templates across all IT and client delivery projects.
• AI & Process Re-engineering: Audit existing delivery workflows to identify bottlenecks; design and deploy AI-driven automation to streamline PMO tracking, reporting, and administrative tasks.
• Delivery Excellence: Monitor portfolio health (budget, scope, timeline, and risk) using data-driven KPIs; intervene early to resolve project escalations.
• Resource Management: Oversee capacity planning and resource allocation, using predictive analytics and tools to ensure optimal utilization of technical talent.
• Strategic Alignment: Partner with executive leadership to align project execution with company business objectives, margins, and revenue targets.
• Tool Optimization: Champion the adoption of modern project management and AI-integrated collaboration tools (e.g., Jira Automation, ClaudeCode
• Mentorship & Leadership: Recruit, train, and mentor a team of Project Managers and Scrum Masters, fostering a culture of continuous learning and tech-forward innovation.

Qualifications & Requirements

• Experience: 10+ years in IT project/program management, with 3+ years in a senior PMO leadership role within mid-size IT services.
• AI & Automation Expertise: Proven track record of implementing AI tools, Generative AI prompts, or low-code/no-code automation workflows to re-engineer and optimize business processes.
• Certifications: Active PMP (Project Management Professional) or PgMP certification is highly preferred. Agile/Scrum (CSM, PMI-ACP) or Lean Six Sigma certifications are a strong plus.
• Technical Acumen: Deep understanding of software development life cycle (SDLC) models, Agile, Waterfall, hybrid delivery, and emerging PMO software technologies.
• Soft Skills: Exceptional stakeholder management, change management capabilities, conflict resolution, and executive-level communication.
• Education: Bachelor’s degree in Computer Science, Information Technology, Business Administration, or a related field.

What We Are Looking For

CLOUDSUFI is seeking a senior, hands-on AI Platform Architect to design and build production-grade platforms for generative AI, agentic systems, data-intensive applications, and analytical workflows. This is a builder-architect role. The successful candidate will define architecture, make technology decisions, develop reference implementations, review critical code and designs, and guide engineering teams from prototypes to secure, scalable production systems. We are looking for a builder-architect with strong engineering judgement and practical delivery experience. The right candidate can define platform direction, evaluate trade-offs, validate ideas through implementation, and guide systems into production. They should be equally comfortable discussing distributed architecture, reviewing code, diagnosing workflow failures, designing evaluation systems, and mentoring engineering teams.

Key Responsibilities-

AI and Agentic Platform Architecture

• Design platforms for single-agent and multi-agent systems supporting planning, reasoning, tool use, memory, delegation, validation, and human approval.

• Define orchestration patterns for deterministic, dynamic, event-driven, and long-running AI workflows.

• Establish clear boundaries between LLM reasoning, application logic, quantitative computation, rules, and human decision-making.

• Evaluate and adopt agent frameworks, model providers, tools, and orchestration technologies based on reliability, flexibility, performance, and cost. Knowledge and Data Systems

• Architect RAG pipelines, document-processing systems, vector search, hybrid retrieval, knowledge graphs, and semantic data layers.

• Integrate structured and unstructured enterprise data from APIs, databases, files, streams, and external platforms.

• Design reusable workflows for research, data collection, transformation, analysis, modelling, validation, and reporting.

• Establish data lineage, provenance, metadata, access controls, freshness, and quality standards. Evaluation, Observability and Governance

• Build evaluation frameworks for accuracy, relevance, groundedness, task completion, tool use, safety, latency, and cost.

• Enable systematic experimentation across models, prompts, agents, tools, retrieval strategies, and orchestration patterns.

• Implement versioning and lifecycle management for prompts, agents, workflows, datasets, knowledge bases, evaluations, and model configurations.

• Establish tracing, monitoring, auditability, guardrails, approval workflows, and production quality diagnostics.

Cloud and Platform Engineering

• Define cloud-native architectures using microservices, APIs, event-driven systems, queues, schedulers, and distributed processing.

• Lead Kubernetes-based deployment, containerisation, CI/CD, Infrastructure as Code, environment management, and release automation.

• Design for horizontal scalability, fault tolerance, resilience, security, data privacy, and high availability.

• Optimise model usage, infrastructure, storage, retrieval, and compute for performance, latency, and cost.

Technical Leadership

• Translate product and business requirements into clear technical designs and implementation plans.

• Build prototypes and reference implementations for high-risk or foundational platform capabilities.

• Review architecture, code, interfaces, data models, infrastructure, and operational readiness.

• Define engineering standards and reusable patterns across AI, backend, data, and platform teams.

• Mentor senior engineers and support teams in resolving complex technical and production issues.

Required Skills and Experience

• 10+ years of experience in software architecture, platform engineering, distributed systems, data platforms, or AI systems.

• Strong hands-on experience designing and building production-grade AI or data-intensive platforms.

• Deep understanding of LLM applications, tool calling, structured outputs, RAG, embeddings, memory, and agent orchestration.

• Strong experience with cloud platforms, Kubernetes, containers, microservices, APIs, event driven architecture, CI/CD, and Infrastructure as Code.

• Experience with relational, document, graph, vector, and distributed data systems.

• Practical experience implementing AI evaluation, experimentation, tracing, monitoring, guardrails, and lifecycle management.

• Strong understanding of security, identity, access control, secrets management, data protection, and production reliability.

• Ability to move effectively between architecture, code, infrastructure, debugging, and technical delivery.

Good to Have

• Experience building enterprise AI copilots, autonomous workflows, research platforms, or analytical systems.

• Experience with knowledge graphs, hybrid search, model gateways, tool gateways, or agent marketplaces.

• Familiarity with LLMOps, MLOps, model serving, feature stores, model registries, and distributed compute.

• Experience supporting real-time and batch data processing at scale.

• Experience comparing and operating multiple commercial and open-source models.

• Prior experience in consulting, client-facing architecture, or complex enterprise platform delivery. 

About the Role

CLOUDSUFI, a Google Premium Partner specializing in data and AI solutions, is seeking a Staff / Principal Tech Lead to drive the technical execution of our Google Data Commons program. This is a high-visibility, horizontal leadership role embedded within the Google ecosystem — based physically at Google's Bangalore office — working in close daily collaboration with Google's core Data Commons engineering team. The Tech Lead is the technical spine of the engagement. They sit across all four delivery areas — Data Engineering, Frontend, ML/AI, and DevOps/Infrastructure — providing architectural direction, resolving cross track dependencies, and ensuring the quality and coherence of everything we ship. Equally critical is the ability to represent CloudSufi in a credible, articulate, and collaborative manner to Google counterparts at every level.

This is a genuinely hands-on role: the successful candidate must be able to write, debug, and reason about Python and GCP code themselves — not only direct others or lean on AI coding assistants — and must be comfortable operating in an open-source, public-data environment without relying, for example, on Google internal (google3) tooling.

Technology Stack & Domain Knowledge

Core / Must-Have

• Relevant experience on Knowledge Graph, Statistical Data and Analytics (any experience with Google Data Commons is a nice to have, but not required)

• Google Cloud Spanner – schema design, distributed transactions, interleaved tables, and performance tuning at scale.

• Google BigQuery – data modeling, partitioning/clustering strategies, query optimization, and integration with downstream consumers.

• Data pipelines – Apache Beam / Dataflow, or equivalent GCP-native ETL tooling.

• Infrastructure as Code – Terraform on GCP; Cloud Build, Artifact Registry, GKE or Cloud Run.

• Demonstrable, autonomous hands-on proficiency in Python and native GCP tooling — able to code and debug independently in a live technical discussion, with AI-assisted development as a complement to (not a replacement for) that proficiency.

• Direct experience working with open, public, and unstructured datasets (e.g. sourcing, cleaning, and integrating public statistics or open data feeds) using open-source or standard GCP-native tooling.

• Solid grounding in knowledge graph vs data warehouse principles, and how to design for schema and data drift in an open-source knowledge graph context.

• CI/CD experience and working with GitHub

• Full stack experience, specially with data centric apps/systems Strong Advantage

• Python (primary language for Data Commons import tooling and ML pipelines).

• TypeScript / React for the Data Commons web frontend and visualization layers.

• Vertex AI, BigQuery ML, or equivalent ML lifecycle tooling.

• Knowledge graph principles, RDF/SPARQL, or statistical data modeling.

• DataCommons Python / REST APIs and the DCID import automation tools.

• Experience with Google's internal engineering culture, tools (e.g. Buganizer, Critique, Cider), or prior delivery inside a Google product or partnership engagement.

Experience & Qualifications Required

• 10+ years of software engineering experience, with at least 3 years in a formal or informal tech lead capacity overseeing multiple workstreams.

• Demonstrable experience delivering production-grade systems on Google Cloud Platform.

• Prior experience working with or for Google — as a Googler, through a Google partnership program, or as a contractor embedded in a Google team — is strongly preferred.

• Exceptional verbal and written English communication skills; able to engage confidently with senior Google engineers and program managers.

• Proven ability to operate across ambiguous, fast-moving programs with multiple parallel tracks.

• Based in Bangalore, India, and able to work on-site at Google's Bangalore office on a regular basis.

• Able to read and interpret an RFP / SOW and connect its terms to a workable technical delivery plan.