This is a super-powered FDE who has world-class engineering talent with the ability to translate it to a business audience. Embeds directly in customer environments. Builds full-stack AI systems for business clients from requirements through production, translating disconnected operations into working software across React, Python, and LLM orchestration on tight timelines.

Product-facing engineer. Builds and owns AI-native applications across the full stack, from React and TypeScript on the frontend to Python, FastAPI, and LLM orchestration underneath, through prototype to production. Works directly with customers to translate operational problems into shipped systems, handling everything from agent debugging to stakeholder demos without a layer in between.

Drives applied research on the hardest problems between current model capabilities and real operational needs, from agent reliability to retrieval over messy data. Sets the agenda, runs rigorous experiments, and closes the loop directly with engineering to move frontier techniques into production within weeks.

Builds and maintains the internal platform that powers every customer deployment, solving multi-tenant infrastructure, observability, and reliability challenges once so they compound across engagements. The systems engineering role behind the product, owning cloud infra, evaluation pipelines, and the tooling that turns field learning into reusable leverage.

Leads complex AI implementations from kick-off to close, keeping priorities, requirements, stakeholders, and delivery milestones clear while partnering tightly with engineering. Translates shipped work into executive-ready business cases, client alignment, and repeatable delivery playbooks so each deployment moves faster and lands with measurable value.