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# Software Engineer, Enterprise Applied AI

- **Company:** Mercor, Inc.
- **Location:** New York, NY, United States
- **Salary:** $145,000.0 - $285,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Python (Programming Language), Cloud Platform System, Enterprise Integration
- **Published:** August 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7dc18b78a3dc7407

## About the Role

* Strong software engineering fundamentals in at least one modern language (Python, Go, Rust, etc.).
 * Experience building and deploying production systems in cloud environments (AWS/GCP/Azure).
 * Comfort working directly with customers and explaining technical concepts to non-technical stakeholders.
 * High ownership mindset with the ability to navigate ambiguity and operate autonomously in high-stakes environments.

## Description

As a Software Engineer, Applied AI on Mercor's Enterprise team, you'll operate at the intersection of engineering, product, and customer success. Engineers on this team are builders first, embedding directly with enterprise clients to design and implement technical solutions that unlock the full value of Mercor's platform while applying strong systems and product thinking where it matters. The work spans everything from architecting integrations and writing production-grade code to deploying scalable solutions in production environments, always tied closely to measurable business outcomes. You'll collaborate with customer stakeholders and internal teams to deliver systems that directly shape how AI-powered human intelligence integrates into complex enterprises.

You will:

 * Embed with enterprise customers to understand technical requirements and business goals.
 * Architect and implement custom integrations, APIs, and workflows on top of Mercor's platform.
 * Deploy scalable solutions in client environments and drive successful launches and expansions.
 * Build internal tools and reusable components that accelerate future deployments.
 * Translate ambiguous enterprise needs into clear technical plans and shipped systems.


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