Engineering Manager, Applied AI
- Location
- San Francisco, CA · On-site
- Job type
- Full-time
- Level
- Director
- Experience
- 6+ years
- Education
- Bachelor's degree
- Listed
- 30 days ago
Skills & highlights for this role
- scalable system design
- AI model evaluation
- engineering team leadership
Also useful
- human-in-the-loop workflows
- multimodal systems
Stated benefits & perks
- Health
- Dental
- Vision
- Equity
- Wellness stipend
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
- Bachelor’s Degree in Computer Science or a related technical degree such as Electrical Engineering, Physics, Mathematics or Statistics
- 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
- Relocation assistance will be provided as needed
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
Benefits
- Bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
About Mercor
Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.
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.
From Mercor's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
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Common questions
Where is the Engineering Manager, Applied AI job at Mercor located?
This Engineering Manager, Applied AI position at Mercor is located in San Francisco, CA (On-site). Always check Mercor's application page for specific state eligibility or relocation policies.
What qualifications are required for Engineering Manager, Applied AI at Mercor?
For the Engineering Manager, Applied AI role, Mercor highlights 6+ years of relevant experience; a bachelor's degree; experience with scalable system design, AI model evaluation, engineering team leadership. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Engineering Manager, Applied AI position at Mercor?
This listing links directly to Mercor's Ashby application page. You can apply directly on Mercor's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.