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 a Senior AI/ML Engineer to own agents, copilots, and platform services end to end—and to raise the engineers around you as you do it.
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 as a fully proficient engineer who takes an ambiguous-but-scoped problem from design to shipped, instrumented software with limited guidance. Building the agent is the easy part; making it reliable enough that a finance analyst trusts it on a Monday morning is the job. That means you care about evaluation as much as features, and you understand that an agent nobody can debug is an agent nobody will keep using.
What You'll Do- Own the design and delivery of features and small services end to end—agents, copilots, and platform components—with limited guidance.
- Build agentic systems properly: orchestration, tool use, retrieval, memory and state, and the evaluations that keep them honest as models and prompts change.
- Define the evaluations, regression tests, and observability for what you ship, and take part in on-call and incident response for systems whose output is not deterministic.
- Contribute to the internal AI platform—agent runtimes, model access and routing, tool interfaces built on open standards such as the Model Context Protocol, and developer tooling—following the paved paths our architect sets, and improving them when they get in your way.
- Partner directly with business stakeholders to scope problems and turn them into well-built, measurable solutions. Understand the workflow before you design for it.
- Mentor early-career engineers through code review, pairing, and design feedback, and hold the quality bar on the work around you.
- You consistently ship well-designed features and services that get adopted in production, with quality, safety, and evaluation coverage you can point to.
- You need little guidance to take a scoped but ambiguous problem all the way to instrumented, working software.
- Early-career engineers around you get better faster because of your reviews and mentorship.
- Engineering Depth: Roughly 4+ years of software engineering experience, with a track record of owning and shipping features or services in production—not just contributing to them.
- Applied AI Experience: Hands-on experience building LLM-powered applications—retrieval-augmented generation, agents and tool use, prompt design—and a working understanding of evaluation and LLMOps practice: prompt and agent versioning, regression testing, and observability for non-deterministic outputs.
- Agentic Tooling: Familiarity with orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalents), Model Context Protocol tooling, vector stores, and runtime guardrails.
- Production Fundamentals: Proficiency in at least one production language (Python, Go, TypeScript, or Java) and comfort with modern cloud-native infrastructure—containers, Kubernetes or serverless, CI/CD, observability stacks.
- Evaluation Instinct: You reach for a golden dataset before you reach for a prompt tweak, and you can tell the difference between an agent that works and an agent that demoed well.
- Clear Communication: You explain technical trade-offs to engineers and to non-engineering stakeholders, and you collaborate well across time zones.
- Integrating with enterprise systems—HRIS, Financial systems, GTM Systems, or similar—including their data models and permissioning.
- Contributing to internal developer platforms or productivity tooling that engineers chose to adopt.
- Agent evaluation and observability tooling (LangFuse, Arize, Braintrust, LangSmith, OpenTelemetry-based tracing, or equivalents).
*This job is located in Bengaluru, India
JR: 2026-7955
#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.
