Staff Product Manager, Compute Platform

DigitalOcean•Seattle, WA

22h•$186,400 - $279,600•Hybrid

About The Position

DigitalOcean is seeking a Staff Product Manager, Compute Platform who is passionate about running managed compute services at scale, specifically App Platform, Serverless Functions, and Container Registry. This role requires a deep understanding that a great platform experience is built on well-run infrastructure. The successful candidate will own the product strategy and roadmap for these managed compute services, encompassing both the developer-facing product and the underlying platform economics, such as workload packing, cost to serve, and the impact of processor and container runtime trends on the roadmap. This position reports to the Director of Product and involves close collaboration with the Hyderabad-based Compute Cloud Services engineering team, as well as peers in Droplet/VPC, Kubernetes, infrastructure, finance, and GTM teams. The ideal candidate will be adept at discussing customer-facing workflows and capacity/margin conversations, trusted by engineering on architectural tradeoffs, and will play a key role in expanding the compute platform PM group in India.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.