AI Engineer (New Graduate)

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.

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.

As an AI Engineer (New Graduate) at Distyl, you will:

• 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

• 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
  

• Help improve Distillery, Distyl’s internal LLM application platform, by building reusable components, tools, and workflows

• Learn best practices for scalable, maintainable AI infrastructure
  

• 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
  

• Assist with evaluating AI systems across accuracy, latency, cost, and robustness.

• Apply feedback from users and metrics to improve system performance
  

• 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

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

• 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)

• 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

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

• Mentorship from experienced AI engineers through hands-on project work, code reviews, and design discussions

• 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.