Sr Technical Lead-Gen AI

Job description

Country/Region: IN Requisition ID: 36267 Work Model: Position Type: Salary Range: Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI # **Title:** **Sr Technical Lead-Gen AI** Description: ## **Area(s) of responsibility** **Experience:** 8+ years | **Team Leadership:** 2+ years **Primary Tech:** Python, GenAI, Agentic AI, LangChain, LangGraph, Azure **Summary** We are seeking a hands‑on **AI/ML Lead** to drive the architecture, development, and scaling of our enterprise **GenAI Platform**, with a strong focus on **LLM gateway strategy** (hosted vs on‑prem), **safety/guardrails**, and **cost/performance optimization**. The ideal candidate has deep experience in **Azure‑based AI/ML platforms**, has led **large engineering teams**, and demonstrates strong technical leadership in **GenAI, agentic systems, Python**, and modern orchestration frameworks such as **LangChain/LangGraph**. This role is suited for a senior technologist who can align strategy, execution, and delivery across complex, end‑to‑end AI/ML lifecycle projects. **Roles & Responsibilities** - Lead design and implementation of an **enterprise LLM gateway**, including hosted vs. on‑prem strategy, model routing, fallback, and performance SLAs. - Architect and deliver **agentic AI workflows** using LangChain/LangGraph with robust observability, evaluation, and safety controls. - Own **safety and guardrails**, including prompt security, PII redaction, content filtering, jailbreak protection, and Responsible AI compliance. - Implement **RAG architectures**, vector search, embedding strategy, and grounding with enterprise data. - Optimize **cost and performance**: token usage modeling, caching, batching, quantization, GPU utilization, and scaling. Oversee end‑to‑end SDLC for AI/ML projects: discovery PoC production- monitoring. - Build and maintain production‑grade systems using **Python**, **FastAPI**, CI/CD pipelines, containers, and Azure cloud services. - Manage and mentor a multi‑disciplinary engineering team; drive hiring, technical reviews, delivery quality, and execution velocity. - Partner with Product, Architecture, and Security teams to define roadmap, assess risks, and deliver business value. - Ensure enterprise‑grade security, governance, and compliance across all AI workloads.