Software Engineer II, AI/ML

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here. We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. We are looking for an early-career AI/ML Engineer to help build the agents, copilots, and internal AI platform that are changing how DigitalOcean operates. DigitalOcean is building the substrate for an AI-native company, and the AI Engineering team is doing that work. It spans three connected pillars: internal AI copilots and agents for teams across Finance, People, Sales, Marketing, Support, and IT; the internal AI platform that powers them—model access and routing, agent runtimes, evaluation harnesses, and the developer tooling around them; and re-architecting business processes across our enterprise systems footprint to be AI-native. Our engineers in the US and India work together across time zones, each owning delivery end to end for their business domains while contributing to the shared platform. You will join the team in India, working alongside senior engineers who will help you grow quickly, with technical direction from our architect. This is a hands-on role for someone early in their career who learns fast, ships pragmatically, and wants to become a strong AI engineer. You will take on well-scoped work with real users on the other end of it, and steadily take on more ownership. What You'll Do Implement well-scoped features and components for agents, copilots, and platform services, with guidance from senior engineers and our architect. Write clean, tested code, and build the evaluations that show an agent behaves the way it should—before and after it ships. Integrate tools and data sources into agentic workflows, using open standards such as the Model Context Protocol. Contribute to the internal AI platform: agent runtimes, model access, evaluation harnesses, and developer tooling. Learn and apply modern AI engineering practice—prompting, retrieval-augmented generation, tool use, evaluation-first development, and observability for systems whose output is not deterministic. Partner with teammates and business stakeholders to turn requirements into working software, and take part in code reviews, design discussions, and on-call as you ramp. What Success Looks Like You deliver well-scoped work on time and to a high quality bar, needing less guidance as you go. What you build gets adopted by internal teams and holds up in production. You show growing fluency in agentic systems, evaluation, and our platform tooling—and start spotting problems before they are assigned to you. What You'll Add to DigitalOcean Engineering Foundation: Roughly 1–3 years of software engineering experience, or a strong new graduate with internships or substantial project work in software and applied AI/ML. Language Fundamentals: Solid fundamentals in at least one production language (Python, Go, TypeScript, or Java), and willingness to work across our stack rather than in one corner of it. Real AI Curiosity: Exposure to LLMs, prompting, retrieval, agents, and tool use—through coursework, internships, or things you built yourself. We care that you have actually made something work. A Growth Mindset: You ask good questions, learn fast, and move without waiting for perfect information. Clear Communication: You can explain your work to engineers and to non-engineering stakeholders, and you collaborate well across time zones. Bonus Points Cloud-native tooling: Git, CI/CD, containers, Kubernetes. Vector stores, retrieval pipelines, or evaluation tooling. An LLM-powered project you took end to end—shipped, used by someone, and instrumented well enough to know whether it…