Description
Key Responsibilities

GenAI & Agentic AI Architecture
Define enterprise reference architectures for Agentic AI and LLM-powered platforms, including:
Single-agent and multi-agent systems
Tool-calling and function orchestration
Memory, planning, and execution layers
Own architectural decisions for Claude / Claude Code and other enterprise-grade LLMs, including model selection, deployment patterns, and cost–latency trade-offs.
Design secure-by-default GenAI systems incorporating:
Guardrails and policy enforcement
Data privacy, PII handling, and prompt safety
Controlled tool execution in regulated settings

RAG, Knowledge & Data Systems
Architect large-scale RAG solutions, covering:
Data ingestion and curation pipelines
Chunking and embedding strategies
Vector databases and hybrid search
Evaluation and feedback loops
Partner with Data Engineering teams to ensure data quality, lineage, observability, and governance for AI-driven systems.

Platform & Engineering Excellence
Drive production readiness of GenAI systems:




API-first design (FastAPI / REST / event-driven)
CI/CD for LLM workflows
Monitoring, evaluation, and cost tracking
Establish engineering standards, reusable frameworks, and accelerators for faster adoption across EXL accounts.
Review and influence cloud architecture (Azure / AWS / GCP) for scalable and compliant AI deployments.

Leadership & Stakeholder Engagement
Act as a technical authority for GenAI across delivery teams and client engagements.
Mentor senior engineers, tech leads, and architects on agentic patterns and advanced LLM engineering.
Partner with clients, product owners, and domain SMEs to shape AI roadmaps, solution designs, and value articulation.

Mandatory Skills & Experience

12+ years of total experience with deep hands-on expertise in Generative AI / LLM-based systems, and solid prior background in Data Engineering or Data Science (mandatory).

Generative AI / LLM Expertise

📌 Agentic/ai Lead/architect With Claude/code/llm Ski Noida (India)
🏢 EXL
📍 India