Agentic AI Architect

Role: Agentic AI Architect 
Location: San Jose, CA
Onsite

(10+ Years Experience)
Role Summary
We are seeking a highly experienced Senior Agentic AI Developer and this role focuses on the development and productionization of autonomous, task-oriented AI agents designed to optimize internal engineering workflows, automate complex problem-solving, and enhance platform efficiency.
Required Qualifications

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

Addition Skills (Good 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.

Key Responsibilities

• Agentic Workflow Design:
• 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.
• Platform Integration:
• Develop and maintain Model Context Protocol (MCP) servers to connect agents to canonical internal documentation and tools, ensuring high-fidelity, grounded responses.
• Tooling & Automation:
• Utilize the Google Antigravity platform and Agent Development Kit (ADK) to build context-aware assistants that integrate with existing IDEs and development tools.
• Productionization:
• Lead the transition of AI Proof-of-Concept (POC) projects into production-ready services, collaborating with Moma and other internal search and productivity teams.
• Architectural Leadership:
• Propose and implement architectural changes to agentic systems to improve reasoning capabilities, reduce latency, and optimize token usage.
• Technical Mentorship:
• Guide junior engineers in adopting "vibe coding" practices and leveraging Gemini-powered agentic tools for effective software development.