About Distyl AI Distyl AI develops production-grade AI systems to power core operational workflows for Fortune 500 companies. Powered by a strategic partnership with OpenAI, in-house software accelerators, and deep enterprise AI expertise, we deliver working AI systems with rapid time to value – within a quarter.

Our products have helped Fortune 500 customers across diverse industries, from insurance and CPG to non-profits. As part of our team, you will help companies identify, build, and realize value from their GenAI investments, often for the first time. We are customer-centric, working backward from the customer’s problem and holding ourselves accountable for creating both financial impact and improving the lives of end-users.

Distyl is led by proven leaders from top companies like Palantir and Apple and is backed by Lightspeed, Khosla, Coatue, Dell Technologies Capital, Nat Friedman (Former CEO of GitHub), Brad Gerstner (Founder and CEO of Altimeter), and board members of over a dozen Fortune 500 companies.

What We Are Looking For At Distyl, we build AI systems using Evaluation-Driven Development —an approach where evaluation is not an afterthought, but the primary mechanism for iterating, improving, and trusting AI behavior in production.

AI Evaluation Engineers focus on designing and implementing the evaluation systems that drive this process. They are hands-on engineers who write production Python code, build evaluation pipelines, and use structured signals to guide system design, prompt iteration, and deployment decisions for real customer-facing AI systems.

This role is for engineers who believe that AI systems only improve when measurement is tightly coupled to development—and who want to apply that philosophy directly to systems that matter.

Key Responsibilities

• Design and implement evaluation frameworks that enable Evaluation-Driven Development for AI systems deployed in customer environments
• Define how system quality is measured in each domain, ensuring that evaluation signals reflect real user needs, domain constraints, and business objectives
• Build and maintain golden test cases and regression suites in Python, using both human-authored and AI-assisted test generation to capture critical behaviors and edge cases. These test suites are treated as first-class system components that evolve alongside the AI system itself

What We Require

• 2+ years of software engineering experience
• Strong Python Engineering Skills: Write clean, maintainable Python and are comfortable building evaluation and experimentation pipelines that run in production environments. You treat evaluation code with the same rigor as application code
• Experience with Evaluation-Driven or Experiment-Driven Development: Experience using structured evaluation or experimentation frameworks to drive system iteration, and understand the pitfalls of overfitting to metrics that don’t reflect real outcomes
• Ability to Translate Human Judgment into Code: Work with subject matter experts to elicit high-quality judgments and encode them into test cases, scoring functions, and graders that scale

What We Offer

• The base salary range for this role is $130K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
• 100% covered medical, dental, and vision for employees and dependents
• 401(k) with additional perks (e.g., commuter benefits, in‑office lunch)
• Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problems
• Ownership of high‑impact projects across top enterprises
• A mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. . We’re grateful for the strong interest in this role. The best way to get your profile in front of our team is to apply directly through our careers page, where all applications are reviewed. Due to the high volume of interest, we’re not able to review or respond to all direct emails or LinkedIn messages. We will be in touch with every applicant once we’ve completed our review, regardless of the decision.