Product Manager, Platform - Cloud Infrastructure (Commercial/Federal)

C3 AI•Redwood City, CA

9h•$150,000 - $190,000

About The Position

C3 AI is seeking a talented Product Manager, Platform - Cloud Infrastructure (Commercial/Federal) to lead the product strategy and roadmap for automating deployments of the C3 Agentic AI Platform across C3-managed, customer, and Federal cloud environments to enable global enterprise and public sector adoption. By driving cross-functional teamwork across Engineering, Cloud Operations, Product, and Field Operations, you will deliver critical capabilities like automated provisioning and deployment repeatability. You will translate sophisticated cloud deployment requirements into clearly defined product features, acceptance criteria, and prioritized backlog items. Managing a comprehensive deployment automation roadmap, you will oversee multi-cloud coverage, data residency requirements, and platform rollout plans across all deployment targets. You will also partner with platform teams to resolve foundational blockers related to tenant onboarding, infrastructure configuration, and operational readiness. Finally, you will serve as a trusted product leader to cross-functional stakeholders and executive leadership, framing trade-offs and prioritizing investments to scale automated deployments across C3, customer, and Federal cloud environments. This role spans both commercial deployments (C3-managed SaaS and customer-managed VPC / BYOC environments on AWS, Azure, and GCP) and Federal deployments (AWS GovCloud, Azure Government, and air-gapped environments) aligned to FedRAMP Moderate/High and DoD IL4–IL6 controls. You will define how a single platform release flows through hardened, compliance-bound pipelines to reach every target environment with predictable quality, security, and time-to-deploy.

Requirements

Bachelor of Science in a STEM field; MBA or Master of Science preferred.
5+ years of product management or technical program management experience, with a strong background in cloud infrastructure, deployment automation, and enterprise or public sector environments.
Excellent verbal and written communication and presentation skills, with the ability to convey complex technical concepts to both executive and engineering audiences.
Strong problem-solving skills and bias for action — able to navigate both business and technical domains and provide clear guidance to internal and external implementation teams.
Deep understanding of modern cloud platforms and compute technologies, including Kubernetes, Apache Spark, Azure, AWS, GCP, and experience with Federal cloud environments such as AWS GovCloud or Azure Government. Working fluency with Kubernetes networking, identity, and multi-tenant isolation patterns is required; hands-on familiarity with at least one of AWS, Azure, or GCP at the deployment-architect level (VPC design, IAM, KMS/HSM, private endpoints) is expected.
Technical proficiency with distributed systems, relational databases, and key-value stores, with the ability to read and understand code and architecture diagrams, though not expected to function as an engineer.
Demonstrated product ownership of Infrastructure-as-Code, GitOps, or CI/CD tooling (Terraform, Helm, ArgoCD/Flux, Crossplane, Tekton, or similar), with a clear point of view on how release engineering should differ between commercial SaaS and Federal pipelines.
U.S. citizenship is required to support Federal customer engagements. Existing or ability to obtain a U.S. government security clearance (Public Trust, Secret, or higher) is a strong plus.

Nice To Haves

Familiarity with AI/ML platform deployment, agentic AI frameworks, or enterprise SaaS deployment models is a strong plus.
Strong plus: experience deploying agentic or LLM-powered workloads — model serving, retrieval/vector stores, tool/MCP integrations, eval and guardrail pipelines — into regulated or air-gapped environments where commercial frontier model APIs are not available.
Direct experience supporting a product through a FedRAMP Moderate or High authorization (or DoD IL4/IL5/IL6 equivalent) — including SSP contributions, control inheritance decisions, POA&M management, and working alongside a 3PAO. Familiarity with NIST 800-53 and CMMC is expected.
Candidates must be authorized to work in the United States without the need for current or future company sponsorship.

Responsibilities

Own the product vision for deployment automation — including roadmaps, product specifications, and release planning — working closely with Engineering, Cloud Operations, Product, and Field Operations across all levels of team planning.
Define and track leading indicators of deployment performance and reliability, and drive prioritization decisions based on insights from platform metrics, deployment reporting, and operational data.
Create and maintain concrete, quantitative, and descriptive profiles of deployment targets and customer environments, including infrastructure configurations, cloud tenancy models, and API and data execution profiles across C3-managed, customer, and Federal clouds.
Partner with Cloud Operations, Platform Engineering, Services, and customers to evaluate and continuously improve deployment automation maturity, repeatability, and operational readiness.
Drive cross-functional alignment across Engineering, Cloud Operations, Field Operations, Marketing, Sales, and Services, ensuring deployment capabilities are well understood, prioritized, and communicated to all stakeholders.
Justify roadmap investments and trade-offs with both qualitative and quantitative evidence, including deployment velocity metrics, customer feedback, and operational impact data.
Drive the customer-managed deployment experience — including private connectivity, customer-managed keys (CMK/BYOK), IAM federation, network egress controls, and Kubernetes-on-customer-cluster patterns — so a customer can stand up and operate C3 in their own VPC with the same reliability bar as C3-managed SaaS.
Set and hold the bar on deployment KPIs — for example, time-to-stand-up a new tenant, deployment success rate, mean-time-to-recover for failed rollouts, and patch latency across the fleet — and partner with Forward Deployed Engineering on the feedback loop from real customer deployments back into the platform roadmap.