AI Engineer (New Graduate)

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 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.

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.
  
  

Qualifications

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.
  

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

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 (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.

Compensation Range: $150K - $170K