Agentic AI Developer

Job Title/Role: Agentic AI Developer

Job Location/Client Location (with City & State): San Jose - California - Onsite

Remote ok (Yes / No): No

Mode: W2 Contract Role

JD:

Senior Agentic AI Developer (8+ Years Experience)

Role Summary:

We are seeking a highly experienced Senior Agentic AI Developer to join the Availability & Reliability Team (ART) under the EPE organization. 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. The ideal candidate will leverage the latest breakthroughs in reasoning and multimodal processing provided by the Gemini 3 family to build scalable, agentic solutions within the Google ecosystem.

Required Qualifications:

● Experience: Minimum 8 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.