Engineering Manager, Enterprise Applied AI

Mercor•San Francisco, CA

5d•$300,000 - $520,000•Onsite

About The Position

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.

Requirements

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 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

AI agents or agent orchestration
LLM applications
Evaluation systems or benchmarking
Enterprise integrations
Workflow automation
Production ML systems

Responsibilities

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