Key Responsibilities
AI-Assisted Development Leadership
- Drive organization-wide adoption of coding agents and vibe coding practices
- Define guardrails, standards, and governance for BFSI environments
- Build playbooks for prompt engineering, code generation, refactoring, test generation, documentation, and secure coding
- Deliver enablement programs including workshops, labs, and brown-bag sessions
- Establish usage analytics and productivity KPIs
Solutioning, Pre-Sales & Proposal Support
Collaborate with sales, pre-sales, service lines, and delivery teamsTailor AI-first roadmaps, demo assets, and POCs / PilotsLead technical solutioning for RFPs / RFIs : architecture options, reference designs, delivery models, and cost estimatesCreate client-facing proposals with measurable success metrics, risk, and compliance alignmentArchitecture & Delivery (LLMs, RAG, Agents)
Architect and deliver agentic systems : tool orchestration, planning / critique loops, memory, multi-agent collaborationOwn end-to-end solutioning : data acquisition, embeddings / retrieval, prompt pipelines, function / tool schemas, APIs / SDKs, UI integrationRAG & Agentic RAG Best Practices
Design advanced RAG pipelines : chunking, hybrid retrieval, rerankers, query rewriting, context compression, caching, grounding, citationsBuild Agentic RAG flows combining retrieval, tool use, and planning loops to maximize accuracy, policy adherence, and cost efficiencyQuality, Evaluation & Observability
Define LLM / agent evaluation metrics : groundedness, factuality, precision / recall, hallucination rate, agent success rate, latency, cost / queryImplement observability : tracing, token / cost accounting, prompt / version lineage, user feedback loops, red-team logsCollaboration & Leadership
Mentor engineers and lead design reviews and AI SDLC standardsInfluence architecture councilsDrive build-vs-buy decisions, vendor evaluations, and cost / latency optimization strategiesSkills Required
Github, Cursor