Design and implement enterprise-grade agent orchestration frameworks
Define standards for agent lifecycle management, state persistence, and context engineering
Lead technical integration of Gemini models via Vertex AI
Develop internal SDKs, abstractions, and reusable components
Build reference implementations and reusable frameworks for high-code agents
Implement logging, tracing, telemetry, and evaluation pipelines for agent performance and reliability
Support engineering teams adopting Gemini Code Assist, CLI workflows, and internal AI development platforms
Optimize inference latency, parallelization, and cost management strategies across agent workflows.

10+ years of experience in software engineering
Significant experience in distributed systems and backend architecture
Deep hands-on coding expertise in Python and at least one of: Go, Java, or TypeScript
Production experience with LLM-based systems, including prompt engineering, tool calling, RAG, embeddings, and agent frameworks
Experience with Vertex AI, Gemini APIs, OpenAI APIs, or similar enterprise AI platforms
Strong understanding of API design, microservices, Kubernetes, and cloud-native architectures
Experience building or integrating orchestration frameworks (e.g., LangChain, LlamaIndex, custom orchestration layers)
Familiarity with vector databases, embedding pipelines, and retrieval strategies
Strong understanding of authentication, authorization, and enterprise security patterns
Proven ability to build reusable platforms, not point solutions.

Principal AI Engineer

Key skills