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.
- 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.
- 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.
- 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 worked.
*This job is located in Bengaluru, India
JR: 2026-7954
#LI-Hybrid
- We innovate with purpose. You’ll be a part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
- We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
- We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
- We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
- DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.
Skills Required
- 1-3 years of software engineering experience or equivalent internships/projects
- Proficiency in at least one production language: Python, Go, TypeScript, or Java
- Exposure to LLMs, prompting, retrieval-augmented generation, agents, and tool use
- Ability to write clean, tested code and build evaluation harnesses
- Experience integrating tools and data sources into agentic workflows (using open standards like Model Context Protocol)
- Clear communication and ability to collaborate across time zones
- Willingness to participate in on-call, code reviews, and design discussions
- Familiarity with Git, CI/CD, containers, Kubernetes
- Experience with vector stores, retrieval pipelines, or evaluation tooling
- An end-to-end LLM-powered project that was shipped and instrumented
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is described as “market‑leading” across medical, dental, vision, and mental health, with 100% employer‑paid life and disability insurance. Wellbeing resources such as an EAP and tools like Headspace, Carrot, and Rightway are also highlighted.
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Equity Value & Accessibility — Ownership opportunities include new‑hire and performance RSU grants alongside an Employee Stock Purchase Plan offered at a discount. These elements are positioned as core components of the total‑rewards package.
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Retirement Support — Retirement programs feature a safe‑harbor 401(k) with employer match and immediate vesting, plus HSA contributions and a suite of FSAs. These offerings are presented to strengthen long‑term financial security.
DigitalOcean Insights
What We Do
DigitalOcean is the Inference Cloud — a full-stack, production-ready cloud platform built to run AI applications with predictable performance, sustainable economics, and radically simpler operations at scale. We are built for teams turning AI into real products — not just training models. Our advantage is not fewer features, but fewer failure modes when operating AI at scale — combining minimal operational overhead, predictable cost efficiency, and a full-stack cloud that works as a system. Hyperscalers are broad by design. Neoclouds are infrastructure-first. DigitalOcean is inference-first — with a real cloud underneath. It combines inference-optimized compute, managed inference software, and integrated cloud capabilities that reduce operational burden for teams running real workloads. Inference is the foundation—not the boundary. Everything else builds on top of it.
Why Work With Us
At DO, we do career-defining work. We innovate with AI and build cutting-edge tech. Our rewards to match that intensity - to motivate you, recognize your impact, and give you what you need to thrive. If you have a growth mindset, like to think big and bold, and are energized by the fast-paced environment, you'll find your place here.
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Remote Workspace
Employees work remotely.
We commit to both remote work and in-person collaboration. These ways of working are dependent on specific roles and are mutually agreed upon by employees. In the US, we are mainly remote. In our APAC locations, we have a hybrid in-office approach.
