Agentic AI Architect

We are looking for Agentic AI Architect for our client in San Jose, CA.

Job Title: Agentic AI Architect

Job Location: San Jose, CA

Job Type: Contract

Job Overview:

Pay Range: $60/hr - $65/hr

Requirement/Must Have:

• Minimum 10+ years of professional software engineering experience with a proven track record in full-stack or backend development.
• Deep practical knowledge of Java and Python, demonstrated through significant development experience.
• Hands-on experience with LLMs, specifically the Gemini family, and their application in agentic workflows, reasoning tasks, and tool-calling.
• Familiarity with Agent Development Kit (ADK), Model Context Protocol (MCP), and agent design in Vertex AI.
• Strong understanding of cloud-native development on Google Cloud Platform.
• Demonstrated ability to lead complex projects from requirement gathering to production release, acting as a strategic liaison between engineering and product stakeholders.

Responsibilities:

• Architect and orchestrate autonomous agents capable of planning, executing, and verifying complex engineering tasks such as code generation, unit test case creation, and automated bug triaging.
• Develop and maintain Model Context Protocol (MCP) servers to connect agents to canonical internal documentation and tools, ensuring high-fidelity, grounded responses.
• Utilize the Google Antigravity platform and Agent Development Kit (ADK) to build context-aware assistants that integrate with existing IDEs and development tools.
• Lead the transition of AI Proof-of-Concept (POC) projects into production-ready services, collaborating with internal search and productivity teams.
• Propose and implement architectural changes to agentic systems to improve reasoning capabilities, reduce latency, and optimize token usage.
• Guide junior engineers in adopting 'vibe coding' practices and leveraging Gemini-powered agentic tools for effective software development.

Nice to Have:

• Experience in Google-proprietary technologies such as Borg, Blaze, Piper, and Critique.
• Cloud-native development on Google Cloud Platform, including experience with Spanner, BigQuery, and Pub/Sub.