Skill: AI Architect
Experience Range : 8 to 15 years
Location: Pan India

Core Competencies
AI/GenAI architecture patterns: RAG, fine‑tuning strategy, agent/workflow orchestration, prompt lifecycle management.
Data strategy & architecture: corpus preparation, embedding design, retrieval strategy, evaluation dataset design.
Governance & guardrails: defining guardrails, standards, and solution reference architectures.
MLOps/LLMOps: CI/CD, model registry, deployment strategy, monitoring approach.
Security-by-design: access control, network boundaries, compliance alignment (platform + integration security).
Roles and Responsibilities
Define reference architecture and reusable patterns for AI/GenAI solutions; enforce consistency across squads.
Lead model/approach selection (RAG vs fine‑tune), define evaluation approach and success metrics.
Drive data & pipeline design (ingest → curate → embed/index → retrieve → generate → evaluate).
Specify and review guardrails (safety, compliance, privacy) and non‑functional requirements (latency, cost, reliability).
Oversee production readiness: regression test bench, deployment plan, monitoring hooks, handover artifacts.

📌 AI Architect (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru