Serve as the lead developer for Artificial Intelligence (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 Artificial Intelligence (AI) products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters.

Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency.

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.

Bachelor’s degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience.

8 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms.

Experience leading technical discovery sessions with executive stakeholders (C-suite) and engineering teams to define AI and hardware infrastructure requirements.

Experience building full-stack solutions that interface with enterprise systems.