What are the responsibilities and job description for the Applied AI Senior Lead position at InfiCare?
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.