AI Engineer, Evaluation

About Distyl AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. What We Are Looking ForAt 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 ResponsibilitiesDesign and implement evaluation frameworks that enable Evaluation-Driven Development for AI systems deployed in customer environmentsDefine how system quality is measured in each domain, ensuring that evaluation signals reflect real user needs, domain constraints, and business objectivesBuild 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 itselfDevelop and maintain evaluation pipelines—offline and online—that integrate directly into system iteration loops. Evaluation results inform prompt design, agent logic, model selection, and release readiness, ensuring that system changes are driven by measurable improvements rather than intuition aloneDefine, calibrate, and operate LLM-based graders, aligning automated judgments with expert human assessments. They investigate where evaluation signals diverge from real-world outcomes and refine grading approaches to maintain signal quality as systems and domains evolveWork closely with Forward Deployed AI Engineers, Architects, Product Engineers, AI Strategists, and domain experts to ensure evaluation frameworks meaningfully guide system development and deployment in productionWhat We Require2+ 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 codeExperience 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 outcomesAbility 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 scaleSystems-Oriented Mindset: Understand how evaluation interacts with prompts, agents, data, and deployment. You design evaluation systems that support fast iteration while maintaining trust and safety in productionAI-Native Working Style: Use AI tools to generate tests, analyze failures, explore edge cases, and accelerate debugging and iterationTravel: Travel between 10-50% of the time, depending on the project, your role and level of interest in doing soWhat We OfferThe base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package100% coverage of medical, dental, and vision insurance for employee and dependentsFlexible time offRetirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resourcesComprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through CarrotComplimentary in-office lunches and snacks providedAccess to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problemsOwnership of high-impact projects across top enterprisesA mission-driven, fast-moving culture that values curiosity, pragmatism, and excellenceDistyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office..#LI-HybridWe believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.LocationSan Francisco; New YorkEmployment TypeFull timeLocation TypeHybridDepartmentEngineering