Principal Product Manager, AI Infrastructure and Orchestration

DataRobot
Washington, Boston, San Francisco, Ontario
Workplace: RemoteFull timeFunction: Product ManagementEducation: bachelorsSkills: ["Technical writing","Prototyping","API product judgment","Cross-functional collaboration","Working without direct reports"]

Own the product layer for deploying and running agent and model workloads in enterprise environments that can’t move to public cloud. Drive design reviews and define the workload and agent runtime APIs, including resource models, lifecycle semantics, placement/capacity, scaling, ingress/routing, governance/auditability, and metering. Lead roadmap direction across two engineering pods while collaborating with teams building on top of the control plane.

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DataRobot
DataRobot
5 days ago

Principal Product Manager, AI Infrastructure and Orchestration

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Own the product layer for deploying and running agent and model workloads in enterprise environments that can’t move to public cloud. Drive design reviews and define the workload and agent runtime APIs, including resource models, lifecycle semantics, placement/capacity, scaling, ingress/routing, governance/auditability, and metering. Lead roadmap direction across two engineering pods while collaborating with teams building on top of the control plane.
Location: Washington, Boston, San Francisco, Ontario
Workplace: Remote
Employment Type: Full time
Job Function: Product Management
Seniority: Mid level

Key Responsibilities

  • •Own workload and agent runtime orchestration for placement, lifecycle, scaling, and isolation on Kubernetes and accelerators.
  • •Define the deployment and workload API: resource model, lifecycle semantics, versioning/backward compatibility, and error behavior customers integrate against.
  • •Drive placement and capacity strategy, including quota/priority across tenants and behavior under contention.
  • •Guide scaling and economics (autoscaling signals, cold start/scale-to-zero, headroom policy, and cost-versus-latency trade-offs).
  • •Set governance/audit and metering/packaging requirements, including reliability/SLOs and operational surface for diagnosing deployments.

Pay and Benefits

Perks:Health InsuranceDentalVisionPaid LeaveParental Leave

Key Requirements

  • •6+ years in product management for infrastructure, developer platforms, or cloud services, with at least 3 years on Kubernetes-based or distributed systems products; 9+ years for principal candidates.
  • •Deep technical understanding of GPU/accelerator behavior, including topology-aware placement and fractional/time-sliced sharing (e.g., MIG), plus utilization and cost trade-offs.
  • •Deep technical understanding of Kubernetes (API server/scheduler, controllers/CRDs, operators, admission/RBAC, device plugins, resource requests/limits, and unschedulable pods).
  • •Experience with multi-tenancy, including isolation models, noisy neighbors, and quota/fairness that can pass customer security review.
  • •Owned a public or platform API end-to-end and can support technical writing/prototyping to validate an API contract early.
Experience:Developer platformsCloud servicesKubernetesDistributed systems
Education:Bachelor's in Computer Science
Skills:Technical writingPrototypingAPI product judgmentCross-functional collaborationWorking without direct reports
Tech Stack:KubernetesCRDsRBACAutoscalingDevice pluginsGPUAcceleratorsMIGVLLMAirflowTemporalInfiniBandRoCETLSDNSCRDOperators

Company Brief

DataRobot
Provides an enterprise AI platform that automates and accelerates the end-to-end data science lifecycle, enabling organizations to build, deploy, and manage machine learning models at scale for business decisioning and predictive analytics.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: Boston, United States
Founded: 2012
WebsiteLinkedIn