Senior Product Manager, Core Platform

C3 AI•Redwood City, CA

8h•$165,000 - $228,000

About The Position

C3 AI is seeking a Senior Product Manager, Core Platform to define and drive the strategy, roadmap, and execution for the foundational platform capabilities that power every C3 AI product and customer-built solution. This is a highly technical, high-leverage role at the center of the C3 AI architecture, spanning data and metadata services, model-driven application development, APIs and SDKs, AI and agent runtime, security and governance, observability, and developer experience. You will turn complex needs from application teams, customers, forward deployed engineers, and platform engineering into reusable platform primitives that make every product faster to build, easier to operate, safer to govern, and more reliable at enterprise scale. Success requires technical depth, structured product thinking, and strong cross-functional leadership. You will partner with Engineering, Architecture, User Experience, Forward Deployed Engineering, Customer Success, Sales, Marketing, and Cloud Operations/SRE to prioritize the highest-leverage platform investments and bring them from concept to production.

Requirements

7+ years of product management, technical product management, technical program management, or equivalent experience, including 4+ years owning technical platform, infrastructure, or developer-facing software products.
Track record shipping platform capabilities used by multiple product teams or enterprise customers, such as APIs, SDKs, data or AI infrastructure, developer platforms, observability, security, deployment, or distributed systems.
Strong technical fluency with enterprise SaaS/cloud platforms, APIs and service-oriented architecture, data and distributed systems, identity and access management, security and governance, AI/ML lifecycle, observability, and reliability.
Ability to work with architecture diagrams, technical specifications, API contracts, and metrics deeply enough to earn Engineering's trust. This role is not expected to code full time.
Excellent product judgment: able to distinguish one-off requests from reusable platform investments, define minimum viable platform capabilities, and make tough trade-offs.
Quantitative mindset and familiarity with product analytics, SQL, dashboards, and data-informed prioritization.
Outstanding written and verbal communication; able to explain deeply technical concepts clearly to executives, engineers, field teams, and customers.
Bachelor's degree in Computer Science, Engineering, Mathematics, Physics, or a related STEM field; equivalent practical experience will be considered.

Nice To Haves

Experience with enterprise AI, machine learning, LLM, or agentic platforms, including model serving, retrieval-augmented generation, vector search, evaluations, guardrails, orchestration, tool integrations, feature stores, or ML Ops.
Experience with cloud platforms, Kubernetes, infrastructure as code, CI/CD or GitOps, observability systems, distributed data stores, and large-scale data technologies such as Apache Spark.
Experience with data governance, lineage, policy enforcement, tenant isolation, key management, privacy, data residency, FedRAMP, NIST, CMMC, or other regulated-environment requirements.
Prior experience in engineering, solutions architecture, forward deployed engineering, data science, technical consulting, or enterprise implementation leadership.
Experience launching platform products from 0-to-1 and scaling them from early internal adoption to broad enterprise or developer adoption.
Experience at enterprise data and AI platform companies such as Palantir, Snowflake, or Databricks.
Advanced degree in a technical field or MBA is a plus, but not required.

Responsibilities

Own the product vision, roadmap, backlog, and release plans for core platform capabilities used across C3 AI products and customer implementations.
Conduct discovery with enterprise customers, application product managers, forward deployed teams, solution architects, engineering leaders, and Cloud Operations/SRE to identify repeated needs and platform gaps.
Translate ambiguous platform problems into crisp product requirements, technical specifications, acceptance criteria, API contracts, and launch plans.
Prioritize platform investments using evidence: adoption metrics, implementation bottlenecks, support escalations, reliability and performance data, strategic customer demand, and long-term architectural leverage.
Partner deeply with Engineering and Architecture to make trade-offs across distributed systems, data architecture, AI runtime, security and governance, deployment models, and operational readiness.
Define and monitor platform KPIs, including API and SDK adoption, time-to-first-value, developer productivity, deployment success, latency and throughput, cost-to-serve, uptime, and support volume.
Drive execution from concept through general availability, including beta and preview programs, field enablement, documentation, launch readiness, and post-launch adoption tracking.
Build durable feedback loops across Product, Engineering, Forward Deployed Engineering, Customer Success, Sales, Marketing, and Cloud Operations/SRE so roadmap decisions reflect real usage and customer outcomes.
Ensure platform decisions support commercial, federal, and regulated customers, including customer-managed environments, multi-cloud and hybrid deployments, data residency, and tenant isolation.