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.
Are you passionate about building the infrastructure that will power the next generation of AI applications? Are you ready to own the GPU strategy behind one of DigitalOcean’s fastest-growing product categories?
DigitalOcean is entering a pivotal moment as we build infrastructure for AI-native companies and the future 100 million developers. Inference is becoming one of the most important layers of the AI stack. Developers need access to the right models, on the right GPUs, with the right latency, pricing, reliability, and scale. At the same time, cloud providers must manage scarce GPU capacity with discipline: maximizing utilization, improving gross margin, selecting the right model mix, and ensuring customers can trust the platform for production workloads.
We are looking for a Principal Product Manager for Inference Engine to define and own the product strategy for DigitalOcean’s inference business. This product leader will be responsible for shaping our GPU strategy, pricing and packaging, utilization framework, and roadmap for serving developers and AI-native companies with high-performance inference at scale.
This is a rare opportunity to help define a high-growth infrastructure business where product strategy, technical judgment, and business economics must come together.
What You’ll Do- Own the GPU strategy for the inference business: Define how DigitalOcean should deploy, allocate, price, and optimize GPU capacity across serverless inference, dedicated inference, batch workloads, and future inference offerings.
- Maximize GPU utilization and margin: Create a clear product and business framework for improving token revenue per GPU hour, reducing idle capacity, reclaiming underutilized infrastructure, and driving better gross margin as the business scales.
- Define the inference product roadmap: Partner with engineering to prioritize capabilities such as prompt caching, autoscaling, batching, latency optimization, observability, dedicated deployments, compliance features, and media model support.
- Balance developer experience with infrastructure economics: Build products that are simple for developers to use while making rigorous tradeoffs around latency, availability, throughput, pricing, and cost-to-serve.
- Create pricing and packaging strategy: Work with finance, GTM, and engineering to define SKUs, pricing models, discounting frameworks, and packaging for serverless, dedicated, and enterprise inference customers.
- Drive customer-backed product decisions: Work directly with AI-native startups, mid-market customers, and strategic accounts to understand model needs, performance requirements, compliance expectations, and deployment patterns.
- Partner deeply with engineering and infrastructure teams: Translate customer demand and business goals into infrastructure requirements across GPU fleet planning, model serving, capacity allocation, performance optimization, and reliability.
- Establish operating metrics for the business: Define and track the metrics that matter, including GPU utilization, token throughput, revenue per GPU hour, latency, error rates, model adoption, margin, customer retention, and capacity efficiency.
- Deep product judgment in infrastructure or AI: Experience building infrastructure, developer platforms, ML platforms, inference systems, cloud services, or highly technical products for developers and enterprises.
- Strong understanding of GPU economics: Ability to reason about utilization, throughput, latency, CapEx, cost-to-serve, gross margin, capacity planning, and workload placement.
- Fluency in modern AI workloads: Familiarity with LLM inference, open-source models, model serving, prompt caching, batching, model routing, media models, latency tradeoffs, and production AI application patterns.
- Technical depth with business orientation: You can work credibly with infrastructure engineers while also making clear product and business tradeoffs for executives, GTM teams, and customers.
- Strong analytical rigor: You are comfortable building frameworks, models, and decision systems that turn ambiguous infrastructure and customer signals into clear product direction.
- Customer obsession: You work backwards from developers and AI-native companies, but you also understand that great infrastructure products must be reliable, performant, simple, and economically sustainable.
- Executive communication: You can explain complex technical and business decisions clearly to senior leaders, customers, and cross-functional teams.
- Ownership mindset: You thrive in ambiguous, fast-moving environments where the product category is still forming and the right answer requires judgment, experimentation, and operational discipline.
- $218,400 - $273,000
*This is a hybrid role
JR: 2026-7822
#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
- Product leadership in infrastructure or developer platforms
- Fluency in agentic AI systems (tool use, code execution, long-running sessions)
- Technical depth in cloud primitives (containers, MicroVMs, sandboxing, IAM, stateful workloads, observability)
- Ability to work with early, demanding customers and translate feedback into product direction
- Strong systems thinking across UX, architecture, security, reliability, and pricing
- Developer empathy for APIs, onboarding, docs, and workflows
- Business judgment connecting product investments to revenue and margin
- Executive communication and cross-functional influence
- Category-building mindset and experience operating in emerging markets
DigitalOcean Compensation & Benefits Highlights
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Healthcare Strength — Health coverage includes medical, dental, vision, and mental-health support plus employer-paid life/AD&D/disability, with multiple plan options and above-average employer contributions. Offerings are described as market-leading and in some cases fully paid to keep premiums low.
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Equity Value & Accessibility — Equity awards (new-hire and performance RSUs) are paired with an Employee Stock Purchase Plan offered at a discount. This ownership component augments cash compensation and broadens participation in company growth.
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Parental & Family Support — Paid parental leave is provided for a defined period and includes a structured, part-time transition-back program. The approach emphasizes a smoother return-to-work experience for new parents.
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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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.
