Staff AI Solutions Engineer

What you'll do

• Define and evolve the technical vision for the governed agent layer, strategy-optimization engine, and simulation environment.
• Write design documents and decision records to translate technical tradeoffs into actionable plans for other teams.
• Integrate the agent layer into the data engineering SDLC to automate ticket routing, planning, and building.
• Build the infrastructure for agentic engineering, including skills, specs, context scaffolding, and shared memory.
• Advance the strategy-optimization engine into a production capability for business metrics like promotional spend and ranking.
• Develop and mature an offline simulation environment to pre-screen product hypotheses against synthetic personas.
• Decompose strategic directions into specific specs and tickets that individual engineers can own end-to-end.
• Mentor engineers across global pods and represent the team technically with vendors and external partners.

What we're looking for

• 8+ years of software, machine learning, or AI engineering experience, including technical leadership of a system other engineers built on.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent industry experience.
• Expert-level Python in production settings, including typing, testing, packaging, and performance awareness.
• Production LLM application experience including agent orchestration, tool and function calling, structured output handling, and retrieval.
• Hands-on experience using agentic coding harnesses and designing skills, context, tool access, and memory for them.
• Strong optimization and experimentation background including search over strategy spaces, deterministic scoring, and A/B design.
• Cloud-native engineering on AWS and hands-on work in a modern data platform such as Databricks.
• Knowledge of sports and/or experience working within a heavily regulated industry (preferred).