AI Tech Architect - 10 years - Immediate Joiners

AI Tech Lead / AI Architect
India (Hybrid) | Data, Analytics & AI | Full-time | Hands-on GenAI Delivery Leadership
About the Role
We are seeking a hands-on AI Tech Lead to lead one or more Generative AI delivery pods for a financial-services client. The role sits between our Senior AI Engineers and the Engagement Manager.
You own the technical direction and day-to-day delivery of your pod: you design the architecture, review the work and unblock it, and you are the technical voice with client architects, platform and security teams. You turn business asks into designs, plans and estimates, and you are accountable for
what goes to production.
Key Responsibilities
Technical Leadership & Architecture
1. Solution Architecture: Own the architecture for GenAI applications (RAG, agentic workflows, document intelligence, evaluation and guardrails) on Azure: Azure OpenAI / AI Foundry, AI Search, Cosmos DB, Functions / App Service, APIM or an AI gateway.
2. Engineering Standards: Set and enforce branching and PR reviews, testing, IaC (Terraform), CI/CD (GitHub Actions), observability, security and cost practices.
3. Trade-off Decisions: Make and document the calls on model choice and routing, retrieval design, latency and cost, and build versus buy, so the team and the client can follow them.
4. Evaluation & Guardrails: Build evaluation in from the start: golden datasets, regression gates on every prompt or code change, LLM-as-judge where it fits, content filters and human review for high-risk outputs.
5. Production Readiness: Run release readiness: UAT support, release notes, rollback plans and production hand-off.
People, Delivery & Client Leadership
● Pod Leadership: Lead a pod of 4-8 engineers (AI, backend, data, full-stack): plan sprints, allocate work, review code and designs, and grow each person. You are the first escalation point for your pod.
● Delivery Ownership: Estimate, plan and track delivery; surface risks and dependencies early (environments, access, client approvals) and drive them to closure.
● Client Technical Lead: Act as the senior technical point of contact with client architects, platform, security and governance teams; lead design walkthroughs, demos and technical decisions.
● Scoping & Communication: Translate vague business asks into scoped solutions and phased plans, push back with options when a request is not feasible, and work with the Engagement Manager on scope, staffing and status.
Required Experience and Qualifications
● Overall Professional Experience: 8-12 years in software or data/ML engineering, with progressive technical leadership.
● AI/ML & GenAI Experience: 3+ years building and shipping Generative AI applications to production.
● Team Leadership: At least 2 years leading engineers: allocation, reviews, mentoring and delivery accountability.Core Technical Competencies
● Generative AI & LLMs: Hands-on depth in LLM application patterns (RAG, hybrid search and re-ranking, agents and tools/MCP, structured outputs) and evaluation/observability tooling (RAGAS, LangSmith, Langfuse or similar).
● Azure AI Platform: Production experience with Azure OpenAI / AI Foundry, AI Search, Cosmos DB, Functions / App Service, Key Vault, private networking and Entra ID / managed identity. AWS experience is acceptable with a clear path to Azure.
● Responsible AI & Security: Content filters and guardrails, prompt-injection and data-leakage risks, PII handling, access
control and audit logging in a regulated (financial services) environment.
● Backend & DevOps: Strong Python (FastAPI, AsyncIO), Docker, Terraform, CI/CD and environment promotion (dev / UAT / prod) with rollback.
● Communication: Clear written and spoken communication with technical and non-technical stakeholders.
Preferred Experience & Education
● Financial services or asset-management domain experience.
● AI gateway / API management (APIM, Kong), model routing and cost control; document intelligence and OCR (Azure Document Intelligence / Content Understanding).
● Working knowledge of React for chat and operations UIs.

Work arrangement
Hybrid