Job description
Technical Program Manager | Fully Remote, United States
A global organisation is looking for a Technical Program Manager to own the delivery of high-impact AI programmes within a large-scale infrastructure environment.
You will drive transformational initiatives end to end, from initial scoping through to production deployment, working at the intersection of artificial intelligence, operational efficiency, and infrastructure at scale.
The programmes you will own are designed to fundamentally change how infrastructure is planned, built, and operated. The measure of success is tangible - fewer manual processes, faster execution, and the ability to scale operations without scaling headcount.
If you have delivered AI-enabled tooling that people actually adopted and used, and you understand why some programmes land and others do not, this role is built for you.
Technical Program Manager Responsibilities
- Take strategic goals from concept to execution. You will translate high-level ambitions into structured delivery plans with clear owners, timelines, success criteria, and decision gates.
- Drive alignment across engineering, operations, and third-party partners. You will not wait for blockers to resolve themselves. You will surface them, escalate them, and drive them to resolution.
- Ensure solutions are built to be used. Adoption, usability, and operational readiness for the people who will work with these systems day to day are as important as the technical delivery itself.
- Own programme delivery for strategic AI and automation initiatives across a complex, multi-team environment. You will set the programme plan, define milestones, manage dependencies, identify risks early, and hold stakeholders accountable for outcomes rather than activities.
- Embed governance into every programme. AI-driven workflows require validation frameworks, human review checkpoints, and rollback capability. You will ensure these are not afterthoughts.
- Define and report on impact. You will establish KPIs covering manual effort reduction, cycle time improvement, and error rate performance, and you will communicate outcomes clearly to senior leadership.
Technical Program Manager Requirements
- Proven programme management rigour. You have managed programmes with multiple workstreams, held cross-functional teams accountable, and driven decisions when ambiguity was high and clarity was needed fast.
- A track record of delivering internal tools, platforms, or automation systems that other teams actually adopted. You understand the difference between shipping something and shipping something that works at scale in the hands of real users.
- Working knowledge of AI and ML integration into operational workflows. You do not need to be a practitioner but you need to engage meaningfully in conversations about data quality, model outputs, automation boundaries, and where human oversight belongs.
- You understand where to place human review gates, how to validate outputs before they reach production, and when full automation is appropriate versus when it introduces unacceptable risk.
- You have worked embedded with engineering teams and can hold your own in technical conversations about APIs, data pipelines, system integrations, and deployment architecture. You do not write the code but you understand the systems well enough to unblock the right decisions.
Ideal Standouts
- Experience owning AI and ML initiatives end to end from problem framing through production deployment and continuous iteration.
- Product ownership experience where you have defined requirements, managed a backlog, made trade-off decisions, and shipped iteratively based on real user feedback.
- Familiarity with data validation challenges and cross-system consistency issues in production environments.
- Experience with infrastructure lifecycle programmes covering design, deployment, provisioning, or operations at scale.
- Phased rollout experience - piloting at limited scope, defining promotion criteria, and scaling based on validated outcomes rather than assumptions.
- Exposure to capacity planning, resource orchestration, or supply and demand signal integration.
- Understanding of MLOps concepts including model versioning, training pipelines, drift monitoring, and continuous improvement cycles.
- Background in field operations enablement, building tools or processes that support on-the-ground technical teams.
If interested, please get in touch with your most up-to-date CV.