Principal Product Manager - Inference Engine

DigitalOcean • Seattle, WA

4d • Hybrid

About The Position

DigitalOcean is seeking a Principal Product Manager for Inference Engine to define and own the product strategy for their inference business. This role is responsible for shaping the company's 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 unique opportunity to define a high-growth infrastructure business where product strategy, technical judgment, and business economics converge.

Requirements

• Deep product judgment in infrastructure or AI, with experience building infrastructure, developer platforms, ML platforms, inference systems, cloud services, or highly technical products for developers and enterprises.
• Strong understanding of GPU economics, including utilization, throughput, latency, CapEx, cost-to-serve, gross margin, capacity planning, and workload placement.
• Fluency in modern AI workloads, including 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, capable of working credibly with infrastructure engineers and making clear product and business tradeoffs.
• Strong analytical rigor, comfortable building frameworks, models, and decision systems.
• Customer obsession, working backwards from developers and AI-native companies.
• Executive communication skills, able to explain complex technical and business decisions clearly.
• Ownership mindset, thriving in ambiguous, fast-moving environments.

Responsibilities

• Own the GPU strategy for the inference business, including deployment, allocation, pricing, and optimization across various inference offerings.
• Maximize GPU utilization and margin by creating frameworks for improving revenue per GPU hour, reducing idle capacity, and reclaiming underutilized infrastructure.
• Define the inference product roadmap, prioritizing capabilities such as prompt caching, autoscaling, batching, latency optimization, observability, dedicated deployments, compliance features, and media model support in partnership with engineering.
• Balance developer experience with infrastructure economics by building simple-to-use products while making rigorous tradeoffs around latency, availability, throughput, pricing, and cost-to-serve.
• Create pricing and packaging strategy for serverless, dedicated, and enterprise inference customers in collaboration with finance, GTM, and engineering.
• Drive customer-backed product decisions by working directly with AI-native startups, mid-market customers, and strategic accounts to understand their needs.
• Partner deeply with engineering and infrastructure teams to translate customer demand and business goals into infrastructure requirements.
• Establish operating metrics for the business, including GPU utilization, token throughput, revenue per GPU hour, latency, error rates, model adoption, margin, customer retention, and capacity efficiency.

Benefits

• Reimbursement for relevant conferences, training, and education
• Access to LinkedIn Learning's 10,000+ courses
• Employee Assistance Program
• Local Employee Meetups
• Flexible time off policy
• Bonus potential
• Equity compensation, including equity grants upon hire and Employee Stock Purchase Program

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed