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
We’re hiring early-career / new-graduate AI Engineers who are excited to build real-world AI systems and grow quickly in a fast-paced, customer-facing environment. As a new grad at Distyl, you’ll be a hands-on contributor from day one, working alongside experienced engineers to design, implement, and deploy production-grade AI systems powered by Large Language Models (LLMs).
This role offers structured exposure to both technical engineering work and real-world business applications of AI. You’ll begin by learning through hands-on development and shadowing customer work, and over time grow into greater ownership of technical decisions and solution design.
This role is ideal for candidates who have strong technical fundamentals, a passion for AI, and a desire to learn how cutting-edge GenAI systems are built and deployed in enterprise settings.
Key Responsibilities
As an AI Engineer (New Graduate) at Distyl, you will:
Build LLM-Powered Systems
Design, implement, and deploy GenAI applications under the guidance of senior engineers
Contribute to prompt design, agent logic, retrieval-augmented generation (RAG), and model evaluation
Help build full-stack AI applications that deliver measurable business value
Learn Through Customer-Focused Work
Gain exposure to customer-facing work by initially shadowing technical conversations and learning how business needs are translated into system design, with opportunities over time to take on more responsibility in technical decision-making and implementation
Partner with senior engineers to understand customer problems and translate requirements into technical solutions
Participate in customer discussions, solution design sessions, and iterative delivery
Contribute to Our Platform
Help improve Distillery, Distyl’s internal LLM application platform, by building reusable components, tools, and workflows
Learn best practices for scalable, maintainable AI infrastructure
Deliver Production-Quality Code
Write clean, well-tested, and observable code that meets reliability, performance, and security standards
Learn how production AI systems are monitored, debugged, and improved over time
Evaluate and Improve AI Systems
Assist with evaluating AI systems across accuracy, latency, cost, and robustness.
Apply feedback from users and metrics to improve system performance
Grow as an Engineer
Continuously develop your skills in LLMs, software engineering, and AI through mentorship, code reviews, and hands-on project work
Learn modern development workflows and deployment practices used in enterprise AI
Who You Are
We’re excited to meet candidates who are curious, motivated, and eager to learn. Strong candidates typically have:
A degree in Computer Science, Engineering, AI/ML, or a related field
Proficiency in Python or TypeScript, with strong software engineering fundamentals
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Academic, internship, or project experience with LLMs or GenAI systems, such as:
Prompting and prompt experimentation
RAG pipelines
Simple AI agents or tool-using systems
Familiarity with LLM tooling or frameworks (e.g., LangChain, LlamaIndex, Agents SDK, or similar), or strong interest in learning them.
Experience building projects end-to-end (school projects, internships, hackathons, or open-source)
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Comfort working in collaborative environments and learning from feedback.
Basic familiarity with cloud platforms (AWS, GCP, or Azure), Docker, or CI/CD is a plus, but not required
What Success Looks Like in This Role
In your first year, you’ll:
Ship production AI features used by real customers
Develop a strong foundation in LLM systems and AI engineering best practices.
Grow into owning meaningful components of customer-facing AI systems
Build confidence working across the full lifecycle of AI development—from problem definition to deployment
Gain structured customer exposure—starting by shadowing technical discussions and learning how business requirements map to technical solutions, and gradually taking on more ownership in both technical execution and customer-facing conversations
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Mentorship from experienced AI engineers through hands-on project work, code reviews, and design discussions
What We Offer
The base salary range for this role is $130K – $150K, 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.
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