Applied AI Senior Lead

Job Title: Applied AI Senior Lead

Location: San Ramon, CA (Hybrid — 3 Days Onsite Required)

Job Type: Contract

Duration: 6 Months+

Experience: 7+ Years

Job Overview

 

Key Responsibilities

 

• Assess where agentic AI approaches genuinely outperform conventional solutions and own the quality bar through automated evals, simulation tests, and regression frameworks integrated with Agent Observability.
• Design and build agentic systems on the Agentic Studio Platform using the Agent Development Kit (ADK), including tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop workflows.
• Define and implement AI governance patterns — guardrails, data lineage, auditability, and responsible AI practices using Agent Identity, Agent Security, and Agent & Tool Registry.
• Implement multi-model routing and fallback (BYOLLM) across Gemini, Claude, LLAMA, and OpenAI, balancing capability, latency, and inference cost.
• Drive adoption through pilots, proofs-of-concept, and scalable production implementations across engineering teams.
• Integrate agents with enterprise data sources across Google Workspace and Microsoft 365 via BYO and vendor-managed MCP servers.

Required Skills

 

• 12+ years of professional software engineering; 2+ years focused on applied AI in production systems
• Proficient in Python and/or Go
• Proven experience building and scaling multi-agent or agent-driven systems in production
• Hands-on experience with Google Gemini Enterprise and Agent Development Kit (ADK)
• Experience with modern agent frameworks: Google ADK, LangGraph, Mastra, Claude Agent SDK
• Experience with observability and eval tooling: Langfuse, LangSmith, Braintrust, Agent Observability
• Strong backend and systems architecture fundamentals — scalability, reliability, cost, deployment
• Google Cloud (Google Cloud Platform) and Vertex AI experience strongly preferred; AWS a plus
• Enterprise API integration: REST, GraphQL, OAuth2, SAML, RBAC
• Comfortable with SQL and NoSQL databases including data access layer design

Preferred Skills

 

• Direct experience deploying agents on Google Gemini Enterprise / Agentic Studio Platform in production
• Experience building custom MCP servers (BYO and vendor-managed)
• RAG architectures: vector databases, embedding models, chunking strategies, hybrid search
• Containerization and orchestration: Docker, Kubernetes, Cloud Run, GKE
• Inference cost optimization across multi-model/BYOLLM deployments
• Experience with AI-powered coding agents: Claude Code, GitHub Copilot, Cursor, Windsurf

Location & Work Model

 

San Ramon, CA — Hybrid, 3 days onsite required. Local candidates strongly preferred as the client may request in-person interviews on a case-by-case basis.

Engagement Details

 

Contract engagement, 6 months or longer. 2 openings available.