Description
Key Responsibilities

Architecture & Solution Leadership
Lead the design of enterprise-grade GenAI and agentic architectures (single-agent, multi-agent, tool-driven systems).
Define reference architectures, reusable frameworks, and best practices for LLM applications across the organisation.
Architect and oversee implementation of end-to-end RAG pipelines:
Data ingestion → chunking → embeddings → vector search → orchestration → response synthesis.
Drive scalability, reliability, cost optimisation, and performance across GenAI platforms.

Agentic & LLM Engineering (Hands-on + Oversight)
Provide technical leadership in prompt engineering, prompt orchestration, and agent workflows (LangChain, LangGraph, etc.).
Guide teams on tool-calling, function-calling, memory handling, and multi-agent system design.
Lead efforts in hallucination reduction, guardrails, safety mechanisms, and output evaluation frameworks.

Platform & Engineering Excellence
Architect production-grade APIs and services (FastAPI/Flask/enterprise microservices) for LLM solutions.




Define MLOps / LLMOps pipelines including CI/CD, monitoring, observability, and evaluation.
Partner with Data Engineering teams to ensure:
Data quality, lineage, governance, and compliance
Seamless integration with enterprise data platforms

Organisation-Level Responsibilities (Critical)

Capability Building & CoE Development
Build and scale GenAI / Agentic AI Centre of Excellence (CoE).
Define standardised frameworks, accelerators, and reusable components to improve delivery velocity.
Drive organisation-wide adoption of GenAI best practices and tooling standards.

Strategic & Stakeholder Leadership
Engage with CXOs, business stakeholders, and clients to translate business problems into AI-led solutions.
Lead solutioning, pre-sales, RFP responses, and client workshops for GenAI prospects.
Influence AI strategy, roadmap, and investment decisions at organisational level.

Gover

📌 Principal Architect Ai Data Engineer Gurugram (India)
🏢 EXL
📍 India