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