Design, build, and maintain backend infrastructure and microservices for AI-driven features. Integrate AI models and services with core systems, develop APIs and data pipelines, and optimize real-time processing for performance, scalability, and resilience. Lead feature development from design through deployment, promote testing and automation, participate in architecture discussions and code reviews, and mentor backend developers.

Build and operate production AI agents, agentic workflows, and AI-enabled developer tools. Design AI systems using agent frameworks, RAG, MCP, tool calling, and guardrails. Develop AI SDLC platforms, observability, tracing, evaluations, and cost analysis. Maintain infrastructure, CI/CD, GitOps workflows, and security controls for AI services. Create internal developer tooling and automation while partnering with engineering and product teams on scalable AI solutions.

Lead the technical direction of an AI platform domain, designing scalable architectures and production-ready agentic systems. Drive decisions involving LLMs, retrieval, tool calling, MCP, evaluation frameworks, and AI infrastructure. Own cross-team initiatives from design through production, establish engineering standards, mentor teams, conduct architecture reviews, evaluate emerging technologies, and balance rapid experimentation with reliability, scalability, and production quality.