Distyl AI develops AI-native technologies that enable humans and AI to collaboratively power operations across the Global Fortune 1000. In just 24 months, we’ve partnered with some of the world’s most iconic enterprises including F100 telecom, healthcare, manufacturing, insurance, and retail companies delivering AI deployments with $100M+ in impact.

Our platform, Distillery , combined with our cross-functional teams of AI Engineers, Researchers, and Strategists, is pioneering AI-native systems of work that solve high-stakes challenges at scale. Distyl is founded and led by proven leaders from companies like Palantir, Apple, and national research labs. We maintain a deep partnership with OpenAI and are backed by Lightspeed, Khosla, Coatue, Nat Friedman, and board members from over 20 Fortune 500 companies.

What We’re Looking For We’re hiring Forward-Deployed AI Engineers at all levels of experience , from early-career builders to senior engineers who can lead large-scale deployments and shape our customers' technical roadmap. Regardless of seniority, every AI Engineer at Distyl is a hands-on contributor responsible for designing, implementing, and deploying production-grade AI systems using Large Language Models (LLMs).

At the most senior levels, our engineers operate as the technical owners of F500 engagements, defining architecture, engaging with enterprise leaders, and leading technical teams to transform mission-critical workflows.

Responsibilities All AI Engineers at Distyl are expected to:

• Design and Deploy LLM-Powered Systems: Build and deploy robust GenAI systems that deliver measurable business value. Includes model evaluation, prompt design, agent/agentic logic, and full-stack application development.
• Engage Deeply with Customers: Work directly with customer stakeholders to understand their most pressing business and technical needs, and turn those into tailored, high-impact AI solutions.
• Build and Improve Our Platform: Contribute to the development of Distillery, our internal LLM application platform, by developing reusable tools, infrastructure, and workflows that scale across customers.
• Deliver Production Quality: Ensure systems are observable, maintainable, and meet rigorous reliability, performance, and security standards.
• Evaluate AI Systems Scientifically: Lead evaluation efforts balancing accuracy, latency, explainability, cost, and robustness.

At Higher Levels Of Experience, You Will Also

• Set technical direction and architecture for multi-million-dollar customer engagements.
• Earn executive trust and guide enterprise engineers through rollout and long-term operations.
• Mentor and up-level Distyl engineers via design reviews, architectural design reviews, leading by doing, and targeted coaching.

Qualifications We believe great AI Engineers come from diverse backgrounds and are unified by deep curiosity, pragmatism, and engineering excellence. We’re excited to meet candidates with:

• Proficiency in Python or Typescript (experience with a diverse set of languages is a plus), with hands-on experience using LLM tooling such as LangChain, LlamaIndex, Guardrails, MCP and Agents SDK.
• Experience building and deploying LLM-powered AI agents in production, including tool use, prompt orchestration, RAG, and long-horizon task execution.
• Deep understanding of agent design patterns, with practical experience in observability, debugging, and human-in-the-loop feedback systems.
• Skilled at solving complex, ambiguous problems using cutting-edge AI techniques to deliver meaningful business outcomes.

What We Offer

• Competitive salary and meaningful equity.
• 100% covered medical, dental, and vision for employees and dependents.
• 401(k) with additional perks (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.

Offices in San Francisco and New York with hybrid collaboration (3+ days/week in-office).