Operations Manager

C3.ai•Redwood City, CA

3d•Hybrid

About The Position

C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. We're looking for an Operations Manager to run the operational backbone of our professional services organization while also building and maintaining the technical infrastructure that makes delivery scalable. This is a hybrid role: half of the job is classic services ops (staffing, forecasting, utilization, delivery cadence), and the other half is hands-on technical work building and managing AI agents and the applications that support delivery teams. This is an internal-facing role — you're building the systems and tooling that make the delivery org run, not sitting embedded with customers. It suits someone who has run operations for a technical organization before, understands why services businesses live and die by staffing and margin discipline, and is also comfortable writing code, configuring agents, and standing up internal tools rather than just spec'ing them out for someone else to build.

Requirements

5+ years in an operations, business operations, or technical program management role within a professional services, consulting, or forward-deployed engineering organization
Bachelor's degree in Business, Finance, or related field of study
Fluency with core ops mechanics: staffing models, utilization tracking, forecasting, and margin analysis
Experience owning a dashboard, reporting tool, or internal application from build through maintenance
Cross-functional communication skills — comfortable presenting to both engineers and executives
Candidates must be authorized to work in the United States without the need for current or future company sponsorship.

Nice To Haves

Experience in a forward-deployed engineering, solutions engineering, or implementation consulting environment is a plus
Familiarity with services-industry benchmarking (utilization targets, delivery velocity metrics, pilot-to-production conversion) is a plus
Experience with enterprise SaaS platforms, low-code tooling, or workflow automation platforms is a plus
Background in change management or org design work is a plus
Direct experience building or configuring AI agents or LLM-based tools (prompt design, tool/function calling, agent orchestration frameworks, MCP or similar protocols)
Data-manipulation skills for building and validating operational reporting
Evaluate and integrate tooling (MCP servers, internal APIs, third-party connectors) to extend what agents can do across the delivery workflow

Responsibilities

Run the operating cadence for the services org: staffing plans, forecasting, capacity planning, and actuals reconciliation against budget
Own the resourcing process — matching engineers and consultants to engagements based on skill, availability, and account priority
Track and report on delivery health across the portfolio: signature-to-first-value timelines, pilot-to-production conversion, margin by engagement, and overinvestment/overrun flags
Build and maintain dashboards and reporting that give leadership real-time visibility into where engagements stand
Manage the escalation process for at-risk engagements, coordinating between delivery teams, account leads, and executive sponsors
Own vendor and subcontractor management where services work is augmented externally
Drive planning cycles (quarterly and annual) — operating plans, headcount models, and org-level capacity math
Design, build, and maintain AI agents that automate internal delivery workflows (e.g., status reporting, staffing recommendations, account health scoring, proposal generation)
Manage the lifecycle of internal applications used by the delivery org — from requirements through deployment and ongoing maintenance
Own uptime, reliability, and iteration for any agent or application you build — this isn't a one-time build, it's a maintained product
Partner with engineering to determine what should be built in-house versus adopted from existing platform capabilities
Prototype quickly to validate ideas before committing engineering resources
Act as the connective tissue between delivery leadership, engineering, and finance — translating operational needs into technical requirements and vice versa
Partner with delivery leads to identify where manual, repeatable work can be automated
Support org design and process changes (restructuring, role definition, delivery principle documentation) with data and tooling
Train delivery staff on new tools and agents as they're rolled out