AI Application Engineer

As an AI App Engineer, you’ll be the hands‑on builder behind the intelligent products that make Sumer Sports unique. You’ll own the end‑to‑end development of LLM‑based applications — from prompt and retrieval design to evaluation, orchestration, and user interface integration. You’ll work within a cross‑functional product pod (with PMs, designers, and Eval Engineers) and partner closely with the LLMOps Platform team and Sports Data teams to ship high‑quality, domain‑aware, and trustworthy AI experiences. Responsibilities Design and build AI‑powered user features: Implement prompt‑based and retrieval‑augmented systems (RAG) that answer complex sports questions and generate insights. Build agents and workflows that combine deterministic logic with LLM reasoning. Prototype and iterate fast: Use prompting, tool orchestration, and retrieval design to rapidly build and refine AI behaviors. Collaborate with Eval Engineers to build golden sets and automate quality checks before release. Work closely with the LLMOps Platform team: Use shared eval frameworks, prompt registries, and model gateways. Provide feedback loops to improve platform reliability, latency, and safety. Integrate with deep learning and data systems: Combine structured stats, tracking data, and video‑derived features into AI‑powered applications. Build APIs and UI layers that expose insights to coaches, teams, and partners. Push the limits of applied AI: Explore how LLMs, retrieval, and deterministic logic can create novel sports analytics tools. Use AI internally to accelerate development (code generation, testing, debugging). Qualifications 5+ years of experience as a Software Engineer, ML Engineer, or AI Developer. Proficiency in Python and TypeScript/JavaScript (Node.js or React). Hands‑on experience with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel, Haystack). Strong understanding of prompt engineering, retrieval‑augmented generation, and evaluation workflows. Ability to design robust backend systems integrating APIs, vector databases, and orchestration layers. Curiosity and creativity to turn ambiguous problems into structured, production‑quality systems. Nice to Have Familiarity with vector databases (Pinecone, Weaviate, Qdrant) and observability tools (Langfuse, Arize Phoenix, Promptfoo). Experience building multi‑agent workflows or LLM tool‑use systems. Understanding of sports data — especially football (tracking data, player metrics, game logs). Experience deploying on Vercel, AWS, or GCP with modern CI/CD. Comfortable working in a pod‑based, cross‑functional environment with designers, PMs, and AI researchers. Benefits Competitive Salary and Bonus Plan Comprehensive health insurance plan Retirement savings plan (401k) with company match Remote working environment A flexible, unlimited time off policy Generous paid holiday schedule - 13 in total including Monday after the Super Bowl #J-18808-Ljbffr