Customer Excellence Technical Program Manager

About the role

The CX Operations Coordinator is the execution backbone of the Customer Excellence team. You own the internal coordination and project management work that keeps customer onboarding on track so Account Managers can stay focused on the strategic customer relationships that drive retention and growth.

Responsibilities

• Own onboarding project plan execution from contract signature to production go-live
• Track open items, chase internal dependencies, and follow up across engineering, solutions, and support teams
• Maintain a real-time view of where every active onboarding stands and surface blockers to the Account Manager early
• Build and improve repeatable playbooks so each onboarding gets faster than the last

Requirements

• Exceptionally diligent, you close loops without being asked
• Strong project management instincts: plans, dependencies, parallel workstreams
• Clear written communicator: crisp updates, no ambiguity
• Process-oriented: you document, templatize, and improve
• 3+ years in operations, project coordination, or implementation

Additional Information

About TrueFoundry Every production AI system - whether it's powering customer support, writing code, analyzing financial data, or diagnosing medical conditions - needs the same foundational infrastructure. A way to route between models. A way to manage tools and integrate them securely. A way to orchestrate agents and enforce governance. A unified compute layer to run it all. That infrastructure layer is being built right now. We're TrueFoundry, and we're building it. The Problem We're Solving Companies are moving beyond simple chatbots to production agentic systems. These systems route between OpenAI, Anthropic, Google, and self-hosted models. They integrate dozens of tools via protocols like MCP. They orchestrate multi-agent workflows where agents coordinate with other agents. The infrastructure to support this doesn't exist yet. You can't just duct-tape together a few API calls and call it production-ready. You need a control plane that handles: Intelligent routing with observability, cost policies, and fallback logic Centralized tool and MCP server management with security and lifecycle controls Agent orchestration with governance and guardrails A unified compute layer to run self-hosted models, custom tools, and agents We've built two products to solve this: AI Gateway is the control plane - five composable components (Prompts, LLM Gateway, MCP Gateway, Guardrails, Agent Gateway) that handle routing, orchestration, and governance. AI Deploy is the compute layer - a Kubernetes-based platform that abstracts ML workloads as standard software primitives, so everything runs on unified infrastructure. We're Series A, backed by Intel Capital and Sequoia. Companies like CVS, Mastercard, Siemens, Paytm, Synopsys, and Zscaler run production AI workloads on our platform.

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Company Intel

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