Engineering Manager, Applied AI

🚀 About Compa

Compa is a venture-backed SaaS startup revolutionizing the future of compensation.

In a dynamic job market with hiring challenges, accountability, and the rise of AI, companies need the best data to stay ahead of industry changes, competition, and costs. Compa has developed the premier real-time compensation data platform, delivering top-tier compensation intelligence to leading enterprise teams.

Compa is a compensation intelligence company built to augment enterprise compensation teams in the era of AI.

Our customers include the world’s biggest companies: Apple, NVIDIA, Tesla, Mastercard, T-Mobile, Sanofi, Moderna, Gilead Sciences, and more.

Location:

While Compa is a remote friendly company, for this role there is a preference for candidates located near one of our offices in Irvine, CA, Denver, CO or Boston, MA.

The Role:

Compa is looking for an Engineering Manager to build and lead our first Applied AI Team. This is a unique opportunity to own and shape how we apply machine learning across both customer-facing products and internal systems. You’ll operate as a player-coach—contributing hands-on to ML projects while building a high-performing team from the ground up.

You'll work closely with Compa’s Co-founder & CTO to define the team’s technical vision, processes, and success metrics. You’ll collaborate cross-functionally with Product, Engineering, CS, and Design to identify high-impact opportunities and ship production-grade ML systems that support comp decisions at the world’s most sophisticated companies.

You’ll be responsible for end-to-end ownership of applied AI initiatives, including model development, MLOps, roadmap planning, infrastructure alignment, and organizational process design.

Minimum Qualifications:

• 7+ years of experience as a technical lead or manager on ML or Applied AI teams

• Proven experience shipping production ML models in customer-facing or business-critical applications

• Strong engineering fundamentals and a “builder” mindset—you’re comfortable rolling up your sleeves to write or review code

• Familiarity with modern ML tooling, MLOps practices, and model evaluation pipelines

• Experience collaborating with Product Managers and cross-functional stakeholders to translate ambiguous problems into technical strategies

• Strong communication and leadership skills, with experience aligning teams and driving delivery

• Ability to create and scale process, tooling, and team practices in a fast-paced, early-stage environment

Preferred Qualifications:

• Experience building ML systems in a startup or zero-to-one context

• Experience partnering with Infrastructure and Data Engineering teams to shape dev environments for ML

• Knowledge of compensation, HR tech, or enterprise SaaS workflows (a plus, not required)

• Exposure to agentic systems, predictive modeling, or real-time data products

• Familiarity with vendor selection, cost planning, or cloud architecture decisions related to ML (in collaboration with leadership)

• A track record of mentoring or developing engineering talent on technical projects

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