Engineering Manager, Enterprise Applied AI

About Mercor Mercor’s mission is to organize human intelligence to power the AI economy. 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 $3 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 Within Mercor, our Enterprise AI organization builds the infrastructure enterprises need to deploy continuously improving production AI systems. Rather than relying on hand-written prompts and manual workflows, we help organizations translate how their best people work into agent behavior, evaluate outputs against measurable quality standards, and create feedback loops that make agents smarter over time.

Our platform combines organizational context, evaluation systems, and quality guardrails into a stack that powers accelerated AI deployment in weeks instead of months. Proven at scale with the world’s leading frontier AI labs, our technology now powers AI deployments across Fortune 500 organizations.

This full-time leadership role sits within Applied AI (the Forward Deployed Engineering team of our Enterprise AI organization) and operates separately from Mercor’s expert network.

We’re hiring Applied AI Leads to build and scale the technical delivery team responsible for deploying Mercor’s Enterprise AI platform for enterprise customers.

This is a highly customer-facing engineering leadership role that is tightly integrated with our Sales/GTM and delivery teams. You’ll lead engineers in the end-to-end technical delivery of production-grade AI systems, working hand-in-hand with customer stakeholders to solve technically complex business problems and contributing to the overall commercial relationship with the customer.

Success is measured by customer outcomes and overall commercial impact, not individual code output. You’ll own technical delivery, coach engineers, remove blockers, and ensure deployments are reliable, scalable, and customer-ready. You have a deep understanding of customer workflows, use case requirements, and acceptance criteria. While you’re expected to be technically credible and capable of hands-on contribution, your primary responsibility is enabling your engineering team to execute.

What You’ll Do

• Partner directly with customers to align technical requirements with business objectives, acting as the critical bridge between engineering and Sales, GTM, and delivery
• Co-lead a Technical team with an Operations counterpart to deliver scalable, production-ready AI systems for enterprise customers
• Translate ambiguous workflows into scalable AI-powered solutions, integrating across enterprise systems, APIs, internal tools, and data sources
• Guide the deployment of AI workflows, agent orchestration, evaluation systems, and continual learning feedback loops
• Hire, mentor, and develop exceptional engineers while establishing rigorous engineering and technical delivery practices as the organization scales
• Work closely with Sales/GTM, Product, Research, and Platform Engineering to bring new AI capabilities into production

What We’re Looking For

• 5+ years building production software systems, with strong software engineering fundamentals in Python, Go, Java, Rust, or similar languages
• 2+ years directly managing technical teams
• Proven track record leading customer-facing technical delivery for enterprise software, AI products, or developer platforms
• Deep experience designing designing distributed systems and cloud-native applications
• Highly comfortable communicating complex technical concepts to both engineers and executive-level customer stakeholders
• Demonstrated ability to lead through ambiguity, coach others, make decisive technical calls, and maintain high execution velocity in unstructured environments

Nice to Haves

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