AI Application Engineer
SumerSports LLC
If you want to work on real AI products from day one, this is a direct path. SumerSports builds football intelligence technology for NFL clubs and NCAA programs. You'll own the full stack of LLM application development—prompt design, retrieval systems, evaluation, and user interfaces—instead of just supporting someone else's work.
Your job is to build. You'll work with product managers, designers, and evaluation engineers to ship features that teams actually use to make roster and salary cap decisions. You're not learning theory; you're solving concrete problems in a domain where domain expertise meets cutting-edge AI.
This fits you if you've shipped code before, understand how LLMs work at a basic level, and want to learn the operational side of AI products fast. Computer science or engineering background is typical, but what matters more is that you can write clean, maintainable code and think in terms of user workflows. Bring a portfolio or GitHub repo.
Apply directly on CareerJumpShip. Include your resume, a brief note on why you're interested in AI application engineering, and a link to your work if you have one.
About this role
SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more. What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football. 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 Originally posted on Himalayas
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