Senior Applied AI Engineer

Teamworks

About The Position

Teamworks is seeking a Senior Applied AI Engineer to build Generative AI (GenAI) features within their Hub product. This role is crucial as the company heavily invests in GenAI to empower sports organizations to make faster, better decisions. The engineer will be responsible for turning this ambition into production-grade reality by shipping features that real teams rely on in high-stakes environments. The position offers the opportunity to own GenAI features that reach a broad user base and shape platform capabilities for other Teamworks products. The role involves designing, building, and shipping production-grade GenAI features, owning these features end-to-end from system design and LLM integration to deployment and monitoring, and building reusable GenAI platform components. Additionally, the engineer will establish best practices for GenAI systems, make architectural decisions balancing various factors in a multi-tenant environment, and partner with cross-functional teams to deliver trustworthy and explainable AI experiences.

Requirements

6+ years of professional software engineering experience building and operating production systems with real customer impact
Proven experience shipping GenAI-powered or ML-enabled features to production, with ownership beyond prototypes or demos
Strong proficiency in TypeScript and Node.js, including building and maintaining backend services and APIs
Solid system design and architecture skills, with experience designing distributed, reliable, and observable services
Strong data reasoning and SQL fundamentals, including aggregation, time-based analysis, and performance considerations
Hands-on experience designing and operating production GenAI systems with prompts, tool interfaces, guardrails, and failure handling in cloud environments (AWS preferred)

Nice To Haves

Experience integrating AI-driven workflows into React-based user interfaces
Familiarity with Infrastructure as Code (Terraform or similar) and cloud-native deployment practices
Experience with observability and evaluation for AI-powered systems (logging, metrics, regression checks)
Exposure to data platforms or lakehouse-style architectures

Responsibilities

Design, build, and ship production-grade GenAI features that help teams explore data, ask better questions, and trust the answers they get
Own GenAI features end-to-end, from system design and LLM integration through deployment, monitoring, and iteration
Build and maintain reusable GenAI platform components that make it easier and safer for teams across Teamworks to ship AI-powered features
Establish and document best practices for building, testing, and operating GenAI systems reliably in production
Make architectural decisions that balance speed, scalability, reliability, security, and cost in a multi-tenant data environment
Partner with Product, Design, and domain subject-matter experts to deliver trustworthy, explainable AI experiences that align with real user workflows