
Staff Product Manager, Compute Platform
DigitalOcean · Posted Oct 29
Cloud infrastructure, virtual machines, managed database, and AI inference services
Get a personal compatibility score
Add a resume for personal matches
About the role
DigitalOcean provides cloud computing products for developers and businesses. The Hyderabad-based Compute Cloud Services engineering team builds the business logic, APIs, and control plane for DO Compute. This role owns product strategy and roadmap for App Platform, Serverless Functions, and Container Registry, balancing developer experience with compute cost, capacity, and pricing.
What you will do
- Own the vision, strategy, and roadmap for App Platform, Serverless Functions, and DOCR, aligned with DO's overall compute platform strategy, and translate them into prioritized, well-scoped features that are simple to use and efficient to run.
- Own the platform economics of these services. Define how apps, functions, and registry storage map onto Droplets and shared compute, track cost to serve per unit of customer workload, and drive utilization, density, and bin-packing improvements with engineering and finance.
- Stay ahead of the compute landscape that underpins the platform, including processor roadmaps from Intel, AMD, and ARM, virtualization and microVM technologies, and container runtimes and isolation models, and translate those trends into platform decisions such as instance sizing, runtime choices, and price/performance tiers.
- Define the end-to-end developer journey across these services, from source repo or container image to a deployed, autoscaled, observable app or function, and remove the seams (auth, networking, registry, logs, billing) that make customers stitch it together themselves today.
- Work backwards from customers. Run discovery with developers, startups, and SMB platform teams, mine support and community signal, and turn it into clear jobs-to-be-done, user stories, and acceptance criteria.
- Own packaging and pricing for platform services, including how compute, egress, build minutes, storage, invocations, and image pulls are metered, how pricing tracks cost to serve, and how the services attach to Droplets, GPUs, managed databases, DOKS, and Spaces.
- Partner with engineering on architecture tradeoffs in the control plane and data plane, such as build pipelines, autoscaling and scheduling behavior, cold start and concurrency for Serverless Functions, registry performance and garbage collection, and multi-region placement.
- Drive performance, reliability, and efficiency outcomes with clear SLOs and cost targets, and champion the fixes that move them.
- Monitor the competitive landscape for managed compute and PaaS offerings, and identify where DO can differentiate on simplicity, price/performance, or both.
- Lead launches end to end with product marketing, docs, sales, and support, and own the results after GA, including adoption, activation, retention, and margin.
Skills used in this role
What the employer is looking for
- 8+ years of product management experience, with a proven track record defining and launching managed cloud compute, PaaS, serverless, or container products, ideally where you owned both the customer experience and the unit economics.
- Strong working knowledge of PaaS, serverless, and container registry models, including buildpack-based deploys, function runtimes and triggers, concurrency and cold start tradeoffs, and OCI image build, storage, and distribution.
- Compute fluency. A solid understanding of the cloud compute landscape, including CPU architectures (Intel, AMD, ARM) and their price/performance characteristics, virtualization and microVMs, container runtimes and isolation, and how these choices affect density, latency, and cost. You will not own the hardware roadmap, but you will make decisions that depend on it.
- Cost and capacity acumen, including understanding of compute, memory, storage, and network cost drivers, the ability to build a cost-to-serve model for a multi-tenant service, and experience turning that model into pricing and utilization targets.
- A strong developer-experience instinct and the ability to specify APIs, CLIs, and console flows that feel simple, with a bias toward defaults that work and escape hatches that do not fight the user.
- Data-driven decision making, with the ability to define the right metrics, read utilization and margin dashboards alongside product dashboards, and change course when the numbers say so.
- Excellent communication and cross-functional leadership, with a record of aligning engineering, infrastructure, finance, and GTM stakeholders across time zones.
Preferred qualifications
- Hands-on Kubernetes experience (cluster operations, workload scheduling, the operator and Helm ecosystem, or building a platform on top of it). You will not own DOKS, but many of our customers' workloads are Kubernetes-shaped, and that background makes for better tradeoffs.
- Prior experience on an IaaS or compute team, such as VM or bare metal product, capacity planning, or fleet efficiency, before or alongside platform work.
- Experience shipping on or competing with Heroku, Render, Fly.io, Cloud Run, Lambda, Fargate, ECR/GCR/ACR, or similar.
- Familiarity with datacenter fundamentals (rack layouts, power and cooling, network design) at the level needed to have a credible conversation with infrastructure teams.
- Prior experience as an early or lead PM for a product area in a new geography.
- Familiarity with DigitalOcean's existing product portfolio.
Benefits and support
- Equity compensation, which may include a new hire equity grant
- Reimbursement for relevant conferences, training, and education, subject to company policy
- Flexible time off
- Local team meetups
- Mental health and well being support
About DigitalOcean
DigitalOcean is an American cloud infrastructure provider and AI-native cloud platform built for developers, startups, and small-to-medium-sized businesses. The company provides simple, scalable virtual machines, managed databases, Kubernetes, and specialized inference engines designed to run modern application and agentic AI workloads.
- Industry
- Cloud Computing
- Company size
- 1001-5000 employees
- Founded
- 2011-06-24
- Location
- Broomfield, Colorado, USA
- Funding stage
- Public Company
Funding
Public Company · $174M raised
- 2013-07-01Seed$3.2M
- 2014-03-01Series A$37.2M
- 2014-12-01Debt Financing$50M
- 2015-07-01Series B$83M
- 2016-04-01Debt Financing$130M
- 2020-05-01Venture Round$50M
- 2021-03-24IPO$775.5M
Leadership
Chief Executive Officer
Chief Financial Officer
Chief Product and Technology Officer
Chief Marketing Officer
Recent coverage
DigitalOcean Newsroom
DigitalOcean Secures $725 Million in Equipment Financing Facility to Fund Capacity Expansion2026-09-10
DigitalOcean Newsroom
DigitalOcean Launches Managed Agents, Bringing Agent Execution, Tool Access, and Inference Together on One Cloud2026-09-21
DigitalOcean Newsroom
DigitalOcean Unveils AI-Native Cloud Built for the Inference Era2026-04-27
DigitalOcean Newsroom
DigitalOcean Acquires Katanemo Labs to Accelerate the Inference Cloud for the Agentic Era2026-04-01