The Role
Drive delivery of an LLM control and routing platform by converting product strategy into sequenced engineering workstreams, managing dependencies and tier-4 triage, enabling CSMs/solution architects, leading internal POCs, and ensuring cross-team execution to ship quarterly commitments.
Summary Generated by Built In
Join Expedient's AI CTRL product team as the technical execution layer between product strategy and engineering delivery. The Technical Program Manager will work alongside the Product Manager and the Engineering Manager, to turn platform vision and market requirements into sequenced, committed engineering workstreams — and then drive the program to ship against them each quarter. You'll be the internal technical authority for our CSM and Solutions Architect teams, the tier-4 triage path when a support issue hits a platform ceiling, and the person who runs internal POCs that define what we build next. You'll be in the architecture decisions and in the room when capability gets defined — technical enough to be credible with engineering, and relentless about turning commitments into shipped software.
Key Responsibilities
Qualifications
Indianapolis, Cleveland, Pittsburgh, or Columbus. Hybrid work model. Regional travel may be required.
Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $130,000 to $175,000
#LI-hybrid
Key Responsibilities
- Drive the Delivery Roadmap: Partner with the Product Manager and Engineering Manager to convert vision and market strategy into sequenced, executable workstreams — then drive the engineering team to ship working code against quarterly commits. You own the delivery plan and cross-team coordination, not the headcount.
- Manage Dependencies and Unblock: Own the critical path across product, engineering, and the commercial team. Surface risk early, manage cross-team dependencies, and remove blockers before they slip a quarter.
- Own Tier-4 Triage: Serve as the technical escalation endpoint for support and engineering issues that hit platform limitations — determining whether a problem is a bug, a configuration gap, or a feature request that belongs on the roadmap, and routing it accordingly. You own the triage and the routing decision, not necessarily the fix.
- Enable CSM and Solutions Teams: Translate AI CTRL platform capabilities into clear, accurate terms for Client Success Managers and Solution Architects — so the commercial team can set the right client expectations and close the right deals.
- Lead Internal POCs: Drive proof-of-concept work with the engineering team to validate new capabilities and de-risk future features before they enter the roadmap.
Qualifications
- Experience: Proven track record driving technical delivery in a production environment — shipping real software against committed timelines across multiple teams. This is a senior role; candidates should have owned the delivery of real technology, not just managed projects around it.
- Technical Expertise:
- Fundamental engineering concepts for agentic workflows and LLM systems — understands how AI agents are architected, orchestrated, and debugged
- LLM platform fluency — model routing and gateways, evaluation/eval frameworks, prompt and context engineering, RAG and vector stores, and the cost/token economics of running models at scale (AI CTRL is an LLM control and routing layer — this is the core domain)
- Application development literacy — can read code, review designs, and assess feasibility well enough to be credible in architecture discussions and to triage escalations accurately
- AI integration into enterprise systems — experience connecting AI capabilities to real business data and workflows (identity, SaaS platforms, APIs)
- Data connectors and data pipelines — understands how data flows from source systems into AI-ready formats
- LLM observability — reads telemetry, spend, latency, and quality metrics to diagnose issues and surface insights, not just generic application logs
- Data governance and compliance awareness — understands the privacy, access-control, and governance constraints of running an enterprise AI gateway
- Key Attributes:
- Platform-agnostic: Evaluates component and vendor choices by fit, not comfort — comfortable comparing approaches across both technical and business dimensions.
- Deeply curious: Spends the first 90 days learning the service offering, the technology stack, and how they connect to market drivers — without being told to.
- Translator: Can walk a CSM through what the vector store does and why it matters for a client use case, then turn around and write the requirements doc for the engineering team.
- Drives to ship: Treats a roadmap commitment as a commitment. Drives the team to deliver working code each quarter, not slide decks about future quarters.
- Leads through influence: Makes delivery happen across teams without org authority — through clear plans, hard prioritization, and trust earned by being technically credible.
Indianapolis, Cleveland, Pittsburgh, or Columbus. Hybrid work model. Regional travel may be required.
Salary for this position is directly related to your own experience, knowledge, and skills. Estimated range for this role is $130,000 to $175,000
#LI-hybrid
Skills Required
- Proven track record driving technical delivery in production environments and shipping software against committed timelines
- Ownership of end-to-end delivery across multiple teams (not just project management around delivery)
- Understanding of agentic workflows and LLM system architecture, orchestration, and debugging
- Fluency with LLM platforms: model routing and gateways, evaluation frameworks, prompt/context engineering, RAG, and vector stores
- Knowledge of token/cost economics for running models at scale
- Application development literacy: ability to read code, review designs, and assess feasibility
- Experience integrating AI into enterprise systems (identity, SaaS platforms, APIs)
- Understanding of data connectors and data pipelines to prepare AI-ready data
- Experience with LLM observability and telemetry: monitoring spend, latency, and quality metrics
- Awareness of data governance, privacy, access-control, and compliance constraints for enterprise AI gateways
- Experience leading internal proofs-of-concept to validate capabilities and de-risk features
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The Company
What We Do
Expedient is a network of data centers offering cloud computing, a wide range of managed services, and network connectivity.
