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Job Description
- Lead the Discovery-to-Deployment Journey: Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Bridge the Enterprise Gap: Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
- Engineer for Production Excellence: Build high-performance evaluation (Eval) pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
- Act as a Product Catalyst: Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
- Upskill and Embed: Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.