Agentic AI Architect

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

Contract

(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 GCP
• 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 GCP 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.