Software Engineering Manager

About the role

You will own the end to end lifecycle of AI quality for WHOOP, translating ambiguous product ideas into reliable, measurable outcomes. You will partner daily with product and engineering leaders to define what success looks like for AI features, ensuring every initiative is backed by observable metrics. You will guide a team of AI and ML engineers, helping them translate complex models into robust, production grade services that members can trust. You will champion rigorous experimentation and documentation, making technical tradeoffs visible and understandable to the entire organization. You will foster a culture where decisions are valued over consensus, where innovation is encouraged, and where psychological safety enables the team to do its best work. You will also manage critical external relationships, ensuring third party integrations meet our high standards for performance and reliability.

Key facts

What you'll do

• Lead a cross skilled engineering team focused on measuring, testing, and improving the quality of AI outputs across WHOOP products.
• Champion the Measure What Matters principle by designing rigorous testing frameworks that track model drift, performance degradation, and real world impact.
• Exercise Decisions Over Consensus by providing clear technical direction, documenting the rationale for major AI architecture choices, and unblocking stalled alignment.
• Manage end to end ownership of third party vendor relationships, evaluating technology partners, overseeing integrations, and tracking partnership performance against key objectives.
• Define the technical strategy, architecture, and design principles for AI quality, ensuring solutions are scalable, observable, and maintainable.
• Drive continuous improvement initiatives that enhance engineering productivity, testing coverage, and the reliability of AI powered insights.
• Provide hands on mentorship and coaching to engineers, supporting career growth, skill development, and alignment with WHOOP values.
• Collaborate closely with data science, product, and operations teams to turn high level objectives into testable hypotheses and measurable success criteria.
• Establish and maintain operational best practices for model monitoring, logging, and alerting to ensure reliable performance in production.
• Represent AI quality considerations in cross functional discussions, balancing user trust, performance, and business goals.
• Build and maintain strong processes for experiment design, result analysis, and documentation to support evidence based decision making.
• Identify risks and edge cases in AI behavior, working with the team to design safeguards and mitigation strategies before release.
• Partner with security and compliance stakeholders to ensure AI quality initiatives meet relevant standards and regulatory expectations.
• Evaluate new tools, frameworks, and research advances, determining their applicability to WHOOP's measurement and quality challenges.
• Lead retrospectives and postmortems focused on AI quality, turning lessons learned into actionable improvements for people and processes.

Requirements

• Hold a Bachelor's degree in Computer Science, Engineering, or a related technical field, or have equivalent practical experience.
• Bring 5 or more years of experience in software engineering, with significant exposure building and measuring the quality of AI or ML products.
• Demonstrate proven experience managing third party vendor relationships and technology partnerships in a technical context.
• Show strong technical skills in applied AI, machine learning concepts, and software deployment lifecycles across development, testing, and production.
• Communicate clearly and effectively, with excellent interpersonal skills and a track record of leading and motivating technical teams.
• Thrive in a fast paced, high growth environment, navigating ambiguity while maintaining focus on measurable outcomes.
• Exhibit a deep passion for wearable technology and its potential to drive meaningful improvements in human performance and health.
• Have direct experience managing AI products at scale, including responsibility for reliability, performance, and user trust.
• Are legally authorized to work in the United States and require no sponsorship for employment at this time.

Nice to have

• Prior experience with AI quality tools, testing frameworks, or model monitoring platforms.
• Background working with wearable sensors, biometric data, or health related time series datasets.
• Experience with modern MLOps toolchains and infrastructure for deploying AI models at scale.

Practical notes

This role is based in Boston, MA, and the successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.