AI Application Engineer

SumerSports

58d • Remote

About The Position

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.

Requirements

• 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 Haves

• 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.

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).

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed