Engineering Manager, Applied AI

MercorSan Francisco, CA
Onsite

About The Position

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.

Requirements

  • 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

Responsibilities

  • 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
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