Teamworks

Computer Vision Engineer

• Own the development and deployment of advanced CV models — object detection, multi-object tracking, camera calibration, and semantic segmentation — for player tracking across multiple sports
• Build and scale high-performance pipelines for video and image data ingestion, processing, and analysis that hold up under the demands of professional and collegiate programs
• Contribute across the full CV/ML lifecycle, from data gathering, model development and training through production deployment, monitoring, and iterative refinement
• Drive R&D initiatives including 3D body pose tracking, real-time analysis systems, and integration with LLM/NLP research — with real latitude to explore within the scope of each project
• Collaborate closely with Software Engineering, Product, and Data Ops to ensure your work is understood, integrated, and used correctly downstream

Data Engineer

• Build and maintain production data pipelines that move performance and product data into the lakehouse with documented schemas, tests, and observability
• Contribute to platform code and Terraform-based infrastructure under the guidance of senior engineers, applying standard patterns and best practices
• Partner with product engineering and domain SMEs to design schema conventions and integrate new data sources cleanly
• Take ownership of components you build, including rotating on-call coverage, responding within SLOs, and contributing runbooks and post-incident learnings
• Anticipate where pipelines can break, build in graceful failure handling, and raise reliability for the components you own

Data Engineer I

• Own the design, implementation, and operation of production data pipelines that consolidate performance data and product telemetry into our lakehouse
• Lead architecture and infrastructure decisions for our lakehouse platform on AWS, including IaC in Terraform, schema design, and multi-tenant isolation patterns
• Drive data modeling for complex entities like time-series performance data, hierarchical org structures, and multi-source athlete profiles
• Build and document the reusable patterns, runbooks, and Terraform modules that let other product teams self-serve new datasets and integrations
• Raise the bar on platform reliability through observability, on-call rotation ownership, and post-incident learning that reduces toil and cost over time
• Partner with product and engineering teams to evaluate and evolve the platform's technology stack as the business scales into new environments
• Participate in our on-call rotation

Senior Data Engineer

Backend Engineer

• Own feature delivery across Compliance, Recruiting, and Camps, breaking complex work into small, shippable increments and seeing them through from design to production
• Design and build internal APIs and data access layers for performant, reliable cross-product data consumption, including the API versioning and service layer work needed to decompose the monolith into a Citadel-style architecture
• Diagnose and resolve critical performance issues in the data import pipeline through measurement, testing, and targeted fixes
• Provide mentorship and technical direction to junior engineers as a natural part of how you work, not as a side responsibility
• Drive code quality through MR reviews, testing practices, and AI-assisted development methods
• Participate in on-call rotation and incident response

Senior Software Engineer, Backend – Java/Spring

Director

• Own the Teamworks visual brand strategy across all three pillars: marketing brand, product brand, and corporate and employer brand, setting the direction and holding the standard across every surface
• Lead design systems governance as living infrastructure, including documentation, versioning, and source-of-truth ownership, building the foundation that enables AI to scale design quality across the company with confidence
• Direct creative output across campaigns, web, digital, social, events, and sales enablement, setting the quality bar and ensuring brand consistency across everything that faces the market
• Shape and build the creative and design function for the next phase of Teamworks, including directing the work of two junior designers and defining the team structure and talent roadmap going forward
• Partner directly with Marketing, Product Design, and occasionally executive leadership to ensure the brand shows up at the right quality across all touchpoints, from product interfaces to investor and employer brand
• Establish creative workflows, intake processes, and project management practices that allow the team to operate efficiently at scale—and raise a flag when brand decisions are being made without sufficient creative input

Director, Brand – Creative

Customer Success Manager

• Own a portfolio of partner accounts across professional and enterprise sports organizations
• Lead end-to-end implementation and adoption strategies
• Build trust-based relationships with performance directors
• Guide organizations in establishing data governance frameworks
• Act as the voice of the customer by sharing feedback

Senior Product Success Manager, Performance – Pro & Enterprise

• Own the full implementation and onboarding cycle for collegiate partners
• Build and manage a growing portfolio of collegiate partners
• Drive product value beyond implementation
• Own the full partner lifecycle independently
• Contribute to internal process improvements

Product Success Manager II, Performance

• Own and deliver backend features end-to-end, contributing to the modernization of AMS’s backend architecture
• Design and optimize API workflows and data models, improving system performance, scalability, and PostgreSQL query efficiency
• Lead efforts to introduce asynchronous processing patterns, eliminate deprecated code, and modernize build and dependency management systems
• Partner with Platform Engineering to enhance CI/CD pipelines, infrastructure, and deployment workflows using tools like Terraform, Kubernetes, and Ansible
• Contribute to architectural decisions and technical direction within the AMS domain, balancing short-term delivery with long-term scalability
• Mentor and support junior engineers, raising the overall technical quality and engineering standards of the team
• Participate in on-call rotations, proactively improving system reliability, observability, and incident response practices

Senior Software Engineer, Backend – Java

Software Engineer

• Own the people leadership of four engineering managers and roughly 15–20 engineers, setting a clear vision, earning buy-in, and driving execution against the team's roadmap
• Lead change management across teams adjusting to new ownership, a shift from front-end/back-end specialization to full-stack development, and evolving roadmap priorities; and get them to a place of stability and productive output
• Ensure technical quality and delivery by bringing system design-level depth to how these teams build, particularly in big data and computer vision contexts, without being a hands-on coder
• Build strong cross-functional relationships with the Platform team and Coaching product leaders across sports verticals, driving roadmap alignment between your teams and the broader organization
• Drive AI adoption across your teams and lead the full-stack engineering transition to completion - two outcomes that will define the shape of this team a year from now

Senior Manager, Engineering

AI Engineer

• 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
• Partner with Product, Design, and domain subject-matter experts to deliver trustworthy, explainable AI experiences that align with real user workflows

Applied AI Engineer

Frontend Engineer

• Own features end-to-end, from technical design and implementation through deployment, monitoring, and iteration in production
• Build and maintain well-tested, maintainable code that meets the reliability bar required for sensitive, real-time workflows
• Contribute to API design in REST and participate in data modeling decisions that need to hold up at scale
• Engage in code reviews and technical discussions, offering thoughtful feedback and raising the quality of what the team ships
• Partner with product and design to translate complex operational workflows into clean, reliable software experiences
• Identify and improve existing systems, including legacy areas that require independent problem-solving to understand and refactor
• Contribute to our microfrontend architecture (module federation), with an emphasis on maintainability, performance, and shared component patterns

Senior Software Engineer, Full Stack – Node, React

• 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

Senior Applied AI Engineer

Data Scientist

• Build and transform new data sources into tables, features, and structures that are easy for the team and our clients to build on
• Develop, extend, and validate models — including event-probability models and athleticism models — ensuring data representation supports both current and future use cases
• Build metrics and analyses that NHL and NBA clients rely on to make decisions, and support client-facing work by digging into the data to answer their questions directly
• Extract meaningful features from high-dimensional tracking and pose data, and update existing models to incorporate new signals as they become available
• Validate models and outputs — your own and others' — with enough rigor that the team can trust what ships
• Write clear reports that communicate technical work to the product team and broader organization