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.
At Distyl, AI Product Engineers build the user-facing applications and workflows through which humans interact with, guide, and improve AI systems. This role is for engineers who care deeply about how intelligent systems behave in practice—and believe that great AI systems are shaped as much by their interfaces, feedback loops, and workflows as by their underlying models.
AI Product Engineers are hands-on builders who work at the intersection of engineering, product, and applied AI. They partner closely with AI Strategists, Forward Deployed AI Engineers, and customers to translate business objectives, domain expertise, and user needs into concrete product experiences that make AI systems more effective over time.
Own the design and implementation of user-facing applications that sit directly on top of AI systems
Build interfaces and workflows for knowledge capture, system configuration, evaluation, and feedback, ensuring that user interactions are tightly coupled to underlying models, data, and evaluation pipelines
Accountable for whether human interactions with AI systems produce high-quality signal that measurably improves system behavior over time
Partner with AI Strategists to understand customer goals, domain constraints, and success metrics, and to turn those inputs into executable product designs
Help shape how domain knowledge and business intent are encoded into workflows, schemas, and interfaces that AI systems can reliably learn from
Work across the full stack—front end, back end, and data—to deliver cohesive product experiences. This includes designing APIs and data models, building services that connect user actions to system behavior, and ensuring that captured feedback can be queried, analyzed, and acted on effectively
Study how humans and AI systems interact in real workflows, identifying where interfaces clarify intent, where they introduce noise, and how design choices affect system performance and trust
Iterate quickly in production, using real user behavior and system outcomes to refine both the product experience and the AI systems it supports
Ownership of shipped product experiences and adapt them as customer needs, business objectives, and AI capabilities evolve
1+ years of experience of software engineering experience
Strong Full-Stack Engineering Skills: Comfortable building across front end (TypeScript/React), back end (Python), and data layers. You can move quickly from prototype to production, and you understand how to design systems that are reliable, maintainable, and easy to evolve
Experience Building Products on Top of AI Systems: Shipped user-facing applications that integrate with LLMs or other AI services. You understand how interface design, data modeling, and workflow structure influence AI behavior, evaluation quality, and system improvement over time
Comfort Operating at the Product–Engineering Boundary: Enjoy working with AI Strategists and domain experts to translate ambiguous business goals into concrete, buildable product workflows. You can reason about tradeoffs between user experience, system constraints, and delivery timelines without needing a separate product manager in the loop
Systems Thinking Across Human and AI Boundaries: Reason clearly about how user actions become structured signal for AI systems. You care about how feedback is captured, how knowledge is represented, and how product decisions affect downstream system performance and trust
AI-Native Working Style: Use AI tools daily to write and debug code, explore designs, analyze data, and automate repetitive work. You actively experiment with new capabilities and incorporate them into how you build and iterate on products
Travel: Ability to travel 10-20%
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.