Teamworks

Product Manager

• Own AI products like "Ask Teamworks" (AI-copilot) and our ecosystem of workflow-embedded AI native agents end to end, unifying the UX across our all-encompassing product suite, taking it from beta to a mature, ecosystem-wide surface
• Own the platform and foundational AI work — the shared infrastructure and standards other product teams build their own AI-native features on top of
• Push AI roadmap beyond the co-pilot experience into deep, agentic workflows that surface recommendations and take action across the ecosystem
• Define the standards for how Teamworks ships AI product, from evaluation methodology to grounding and citation behavior, and help other PMs adopt them
• Own the metrics that prove it's working, including query success rate, time-to-answer, daily active usage, and NPS, and turn what you learn into the next quarter's roadmap

Senior Product Manager, AI

People Operations

• Own US and global benefits administration end to end
• Serve as the primary point of contact for employee benefits questions
• Manage leave for US and global employees
• Lead the annual open enrollment process
• Partner with Finance and payroll to scale proper use of our HRIS

People Operations Coordinator, Benefits & Leave

Customer Support

• Become deeply knowledgeable about the Teamworks product suite
• Own a queue of support tickets across AMS, Nutrition, and Strength & Conditioning, triaging and resolving issues based on severity and business impact.
• Gain an understanding of our customers' challenges and needs in order to troubleshoot and solve complex problems in a prompt and friendly manner.
• Fulfill technical requests including workflow configuration, dashboard and visualization building, third-party integration setup, data uploads, template creation, workflow customization, and general troubleshooting.
• Communicate clearly and responsively with customers, owning all correspondence from initial contact through resolution.
• Handle sensitive information, including athlete health data, and enforce data security measures to protect all information.
• Coordinate with internal stakeholders across Product and Engineering to surface bugs and customer feedback, providing thorough documentation when escalating, and ensuring products are improving and customer needs are being met.
• Contribute to internal process improvements that keep team KPIs healthy as the business scales.
• Participate in a rotating schedule for weekend coverage during high-stakes customer projects.

Customer Support Specialist – Performance, North America

• Own a portfolio of partner accounts across professional and enterprise sports organizations.
• Lead end-to-end implementation and adoption strategy for the Nutrition product.
• Build trust-based relationships with dietitians, performance directors, and medical staff.
• Guide organizations in establishing data governance frameworks, workflow standards, and nutrition dashboards.
• Act as the voice of the customer by sharing feedback and insights across Product, Engineering, and Customer Success.
• Leverage AI tools to improve the quality and efficiency of your work.
• Monitor account health in Gainsight, flag critical alerts proactively, and develop strategies for renewal and product growth.

Senior Product Success Manager, Nutrition Pro & Enterprise

General

• Own the full client lifecycle for MLB and NCAA partner teams
• Build and maintain a unified client health dashboard
• Drive NCAA trial program outcomes
• Validate model outputs and platform releases
• Partner with data scientists and engineers to design statistical validation plans
• Contribute to MLB sales efforts by developing customized materials
• Feed partner insights back into the product roadmap

Product Scientist II, Baseball

Data Engineer

• Define the technical architecture and platform standards for our lakehouse on AWS: distributed cloud architecture, schema conventions, multi-tenant isolation, and integration design
• Lead design and delivery of the production pipelines that consolidate performance and product data, and own data modeling for complex entities (time-series, hierarchical, multi-source) so the models serve products, analytics, and ML
• Introduce just enough data governance, ownership, and stewardship to raise our data maturity, and lay the catalog and semantic-layer foundation that analytics, ML, and AI agents can reason over
• Author and maintain the Data Platform playbook (reusable patterns, ADRs, runbooks, Terraform modules) with data quality and reliability built in, so product teams can self-serve new datasets and integrations
• Lead delivery end to end, from requirements and planning through coordinating workstreams and translating status to senior leadership and non-technical partners
• Mentor engineers across levels, raise the bar through design review and on-call ownership, and be the engineering voice shaping the platform roadmap

Staff Data Engineer

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

• 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