Forward Deployed AI Engineer

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, Forward Deployed AI Engineers build and operate AI systems that deliver real business value inside customer environments. This role is for engineers who thrive in ambiguous problem spaces, take ownership of outcomes, and are excited to work directly on production AI systems that must perform reliably under real-world constraints.

Forward Deployed AI Engineers are hands-on builders who design, deploy, and iterate on end-to-end AI systems. They work close to customers to understand real requirements, translate them into concrete system designs, and continuously improve system behavior through evaluation, iteration, and integration. Their focus is not on demos or experiments in isolation, but on making AI systems work in practice.

Key Responsibilities

• Own the behavior and performance of AI systems deployed for customers

• Design and implement compound AI workflows that combine models, agents, retrieval, evaluation, and execution into coherent, production-ready systems aligned with real SME needs

• Operate on live systems, measuring behavior, identifying failure modes, and iterating rapidly to improve quality, reliability, and usefulness. This includes designing prompts and agent logic, building evaluation frameworks, integrating feedback loops, and using AI-driven tools to accelerate debugging and experimentation

• Integrate AI systems into customer data platforms, APIs, and existing applications. You'll make pragmatic system design decisions that balance speed, robustness, and maintainability, and ensure systems remain understandable and operable over time

• Work directly with customer stakeholders—often in high-visibility settings—and are expected to reason clearly about system behavior, tradeoffs, and limitations.

• Take accountability for outcomes in production and adapt systems as requirements evolve

What We Require

• 2+ years of software engineering experience

• Ownership Mentality for AI Systems: You take responsibility for whether an AI system actually delivers its intended value in production. You are comfortable making independent technical decisions across system design, evaluation, and integration, and owning the results of those decisions

• Experience Building AI Systems, Not Just Calling APIs: Built applications powered by LLMs or other AI models and are comfortable composing multiple components—prompts, agents, tools, retrieval, evaluators—into end-to-end systems. You reason about system behavior holistically rather than treating models as black boxes

• Strong Engineering Fundamentals: Write clean, maintainable Python and are comfortable building and operating real systems. You understand core engineering concepts like versioning, debugging, testing, and performance, and can build systems that hold up under real usage and scrutiny

• AI-Native Working Style: Use AI tools daily to write and debug code, explore designs, analyze data, and automate repetitive work. You are curious about new model capabilities and techniques, and actively incorporate them into how you build and iterate on systems

• Comfort in Customer Environments: Able to work directly with customer teams, ask good questions, and adapt quickly to new domains. You communicate clearly about system behavior and limitations, and can operate effectively in high-trust, high-visibility situations

• Travel: Ability to travel 25-50%

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.