Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI). Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters as part of an expert team.
Design and deploy production-grade agentic developer workflows on Google Cloud's AI stack, executing large-scale refactors, language migrations, Specification-to-Pull Request pipelines, and automated review/incident-to-fix loops. Embed with customer's staff engineers and leaders to identify core SDLC bottlenecks, such as legacy migrations, test coverage, review latency, or onboarding friction, and define success metrics.
Integrate Google’s agentic systems into the customer's existing ISV and tools (e.g., Teamwork Graph, GitLab, ServiceNow, Slack) leveraging MCP and A2A protocols.
Job description provided by Google.
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