Serve as the lead developer for AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable return on investment.

Architect and code the connective tissue between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.

Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous 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 product feature requests for the Engineering teams.

Drive engineering excellence by mentoring talent, co-building with customer teams, and influencing cross-functional strategies to uplevel organizational technical capabilities.

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

6 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.

Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.

Experience architecting scalable AI systems on cloud platforms e.g., Google Cloud Platform (GCP).

Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.