Serve as a team lead and developer within the strategic AI partner for AI applications, working with partner’s teams to transition from rapid prototypes to production-grade, replicable agentic workflows (multi-agent systems, MCP servers) that drive measurable Return on Investment (ROI).
Co-build with a strategic AI partner’s own FDE teams to instill Google-grade development best practices, ensuring project success and high end-user adoption.
Help partners to build their own agentic delivery capabilities to set them up for long-term success, focusing on the ROI at customer engagements ensuring customer activation.
Build high-performance evaluation pipelines and observability frameworks to ensure partner developed agentic systems meet requirements for accuracy, safety, and latency.
Identify repeatable partner and field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams.
Minimum qualifications
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience with software development using Python or similar coding languages.
Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
Experience taking production-grade AI-driven solutions from conception to launch for customers.
Experience leading technical discovery sessions with customers.
Preferred qualifications
Master’s degree or PhD in AI, Computer Science, or a related technical field.
10 years of experience with software development using Python or similar coding languages.
Experience in customer facing role, engaging with, and presenting to, technical stakeholders and executive leaders.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
Knowledge of Large Language Model native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience with software development using Python or similar coding languages.
Experience architecting AI systems on cloud platforms (e.g., Google Cloud Platform).
Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
Experience taking production-grade AI-driven solutions from conception to launch for customers.
Experience leading technical discovery sessions with customers.
