Enterprise AI Architect

Job title - Enterprise AI Architect

Location – Bay Area, CA – Onsite (Only Local Candidates)

Experience Range

12–15 years of experience in AI/ML-related roles, with strong experience in LLMs & Agentic AI (architecture, governance, platform strategy).

Primary (Must have skills)* - To be Screened by TA Team

3–5 years: Experience designing enterprise AI solutions including Gemini/Vertex AI, agent applications, RAG pipelines, grounding/data connectors, LLM orchestration, and model governance.

5–7 years: Strong expertise designing ingestion frameworks, APIs, data normalization, semantic search, attribute‑level & record‑level access control, PII masking, and connector factory patterns.

Hands‑on experience with Vertex AI, Gemini Enterprise (Agentspace), Vector Search/Matching Engine, Functions, Cloud Run, IAM, Secret Manager, Kubernetes.

2–3 years: Experience defining multi‑agent coordination flows, intent routing, graceful handoff, context propagation, LangChain/LangGraph/DSPy patterns.

Strong knowledge of embedding pipelines, grounding strategies, retrieval optimization, hybrid search, schema‑aware context construction.

2–3 years: Hands‑on experience implementing LLM governance, safety patterns, content moderation, policy enforcement, auditability, model drift tracking.