Engineering Manager, Applied AI
Role Overview
This senior-level Engineering Manager role leads a team of 6-10 engineers in the Applied AI organization, focusing on building and scaling systems that improve AI model quality through evaluation infrastructure, annotation products, and multimodal capabilities. Day-to-day responsibilities include managing team growth, driving technical direction for complex AI systems, and partnering with product, research, and external AI labs to directly impact frontier AI development. The hire will have high ownership in shaping engineering practices, hiring processes, and measurable outcomes that enhance model performance and operational efficiency.
Perks & Benefits
The role is fully remote, though the company prefers locations in San Francisco or New York, implying potential time zone alignment with US-based teams. It offers high ownership and impact, with opportunities to build partnerships with leading AI labs and shape a rapidly scaling organization at the intersection of engineering, product, data, and AI. Career growth includes coaching and developing high-potential engineers, defining engineering management practices, and working in a fast-paced, ambitious culture focused on AI advancement.
Full Job Description
About Mercor
Mercor is defining the future of work. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.
Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
We’re hiring Engineering Managers to lead teams within our Applied AI organization.
Applied AI builds systems that directly improve model quality, including evaluation infrastructure, annotation products, and emerging multimodal capabilities. You’ll lead a team of engineers, partner with product and research, and help define how Mercor stays at the frontier of AI.
You will also build partnerships with leading AI labs and directly contribute to improving the quality of frontier models through data, evaluation, and systems.
This role requires high ownership and abstraction: setting direction, driving outcomes, and staying hands-on while leading.
What You’ll Work On
Build and scale teams
Manage and grow a team of 6–10 engineers
Coach and develop high-potential engineers
Establish strong ownership, culture, and execution standards
Shape the team: define hiring processes, establish engineering practices, and scale a high-performing team from the ground up
Drive Applied AI systems and outcomes
Drive insights and methodology behind evaluation systems that benchmark and improve model performance
Lead development while driving improvements in data quality, operational efficiency, system stability, and scalability
Scale products that generate high-quality training data and improve human-in-the-loop workflows
Own technical direction
Lead system design for complex AI systems
Stay close to the technical work and guide engineers through ambiguous problems
Translate high-level AI goals into clear engineering roadmaps and execution plans
Operate across a broad scope
Partner with product, research, operations, and external AI labs
Work across systems, data insights, and custom partnerships to drive model quality
Shape the organization
Introduce lightweight processes as the organization scales
Hire and develop strong engineering talent
Help define engineering management at Mercor
What We’re Looking For
6–10 years in engineering; 2–3+ years managing teams
Strong background in building scalable systems
Ability to lead in ambiguous environments with sound technical judgment
Proven ability to coach engineers and drive execution
Strong ownership mindset with pragmatic decision-making
Who Thrives Here
We’re looking for engineering leaders who take ownership in ambiguous environments, make pragmatic decisions, and consistently deliver measurable impact.
Success Metrics
Build high-performing, well-supported teams
Hire and retain strong engineers
Improve team velocity and execution quality
Contribute to systems that measurably improve model performance
Location
San Francisco (preferred) or New York
Why This Role
Direct impact on frontier AI development
Build partnerships with leading AI labs and shape how frontier models improve
High ownership across team, systems, and hiring
Opportunity to shape a rapidly scaling organization
Work at the intersection of engineering, product, data, and AI
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