IN_Senior Manager_GenAI Technical Lead_Alliances_IFS_Gurgaon/Bangalore

Job description

**Job Description & Summary** : This is a senior role to help run and grow the GenAI Experience Lab. It covers four areas: forward-deployed engineer, lead developer, solution architect, and GenAI advisor to clients. You will design and build production-grade GenAI solutions in our priority sectors and competencies, lead the engineering team, set the technical direction, and work with clients to identify and shape new work. You will stay hands-on with architecture and delivery while also operating at a senior, client-facing level. Proofs of concept support client work but are secondary to building and delivering solutions. PwC India's GenAI Experience Lab designs and builds generative AI solutions for clients in the sectors and competencies the firm focuses on. We also run workshops to train client and internal teams on GenAI, and build proofs of concept to test ideas before they are taken forward. **Job Position Title** : IN\\_Senior Manager\\_GenAI Technical Lead\\_Alliances\\_IFS\\_Gurgaon/Bangalore **Responsibilities** : - Design and build production-grade GenAI and agentic solutions aligned with our priority sectors and competencies, owning architecture and delivery end to end. - Work as a forward-deployed engineer and advisor: work on-site with clients to understand their business, shape solutions, and support adoption. - Own solution architecture for GenAI systems: retrieval pipelines, multi-agent orchestration, evaluation harnesses, and LLMOps platforms, across Azure, AWS, and GCP. - Identify and shape new work with clients: value-case sizing, proposals, SOWs, staffing, and CXO conversations. Take selected solutions from build to scaled deployment. - Architect agent systems (LangGraph, CrewAI, AutoGen, Semantic Kernel, MCP / A2A) and apply agent patterns (ReAct, Plan-and-Execute, Reflexion, supervisor/worker, hierarchical agents, long-horizon memory, human-in-the-loop). - Set up LLMOps / AIOps and cost management for GenAI: CI/CD for prompts and agents, model registry, evaluation gates, canary and shadow deployments, drift detection, and cost tracking. - Design data and retrieval layers across relational (PostgreSQL, Snowflake, Databricks), vector (Pinecone, Weaviate, Qdrant, Milvus, Azure AI Search), and knowledge graphs (Neo4j, Neptune, TigerGraph). - Build proofs of concept where they help win and de-risk client work. - Lead workshops and executive briefings; build accelerators, reusable IP, and points of view on agentic AI. - Lead and grow the engineering and consulting team; set standards; mentor Managers and Senior Associates. **Mandatory skill sets** : - ~12+ years across software engineering, solution architecture, and GenAI / AI delivery, with a recent focus on GenAI. - Production experience delivering multiple enterprise GenAI systems with measurable adoption, SLAs, and cost controls. - Ability to work across all four areas of the role: hands-on engineering, lead development, solution architecture, and client advisory. - Strong knowledge of agent patterns, retrieval engineering, and the full GenAI stack (model providers, vector databases, agent frameworks, LLMOps). - Experience in AI consulting and client management: discovery, value sizing, CXO presentations, and managing scope, risk, and commercials. **Preferred skill sets** : - Contributions to open-source GenAI projects, papers, or tech blogs. - Experience with voice agents (LiveKit, Pipecat, Vapi), browser / computer-use agents, or robotics. - GPU optimisation: quantisation (GPTQ, AWQ, GGUF), KV-cache tuning, speculative decoding. - Cloud certifications (Azure AI Engineer, AWS ML Specialty, GCP ML Engineer). **Years of experience required** : 12+ Years **Education qualification** : - B.Tech in Computer Science / IT (strongly preferred). - MBA from a Tier-1 / 2 B-school (for example IIM A/B/C/L, ISB, XLRI, FMS, MDI) strongly preferred. - Management-consulting background and a track record of enterprise AI / agentic AI delivery. - Clear written and verbal communication, including with senior stakeholders and, where relevant, regulators. **Tech Stack You'll Work With** - Cloud & AI Platforms: Azure (OpenAI, AI Foundry, AI Search, ML, Functions), AWS (Bedrock, SageMaker, Lambda, OpenSearch), GCP (Vertex AI, Gemini, Agent Builder, BigQuery) - LLMs & SLMs: GPT-4o/5, Claude Opus/Sonnet 4.x, Gemini 2.x, Llama 3.x, Mistral, Mixtral, Phi, Qwen, DeepSeek, Command R+ - Agent Frameworks: LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, Haystack, DSPy, Pydantic AI, MCP, A2A - Vector & Graph: Pinecone, Weaviate, Qdrant, Milvus, pgvector, Azure AI Search; Neo4j, Neptune, TigerGraph - DevOps & Infra: Docker, Kubernetes, Terraform, GitHub Actions, Azure DevOps, Argo, Airflow, Kafka, Redis - Languages: Python (primary), TypeScript / Node, SQL; FastAPI, Pydantic, async patterns