Requirements

Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
5 years of experience with software development using Python or similar coding languages.
Experience taking production-grade AI-driven solutions from conception to launch and architecting AI systems on cloud platforms (e.g., Google Cloud Platform (GCP)).
Experience building pipelines for structured and unstructured data using both vector databases and RAG-like architectures to power enterprise AI solutions.
Experience leading technical discovery sessions.

Nice to Haves

Master’s or PhD in AI, Computer Science, or a related technical field.
Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, ADK) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
Knowledge of "LLM-native" metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.

Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows that drive measurable ROI.
Architect and code the "connective tissue" between Google’s AI products and customer's live infrastructure.
Build high-performance evaluation pipelines and observability frameworks for agentic systems.
Identify repeatable field patterns and friction points in Google’s AI stack.
Co-build with customer engineering teams to instill Google-grade development best practices.