Enterprise AI Delivery Operations Lead, Scale AI

• 3-5+ years of experience in delivery management, program/technical program management, or operations in a fast-paced, high-ambiguity environment (startup ops, consulting, or military logistics backgrounds can be strong fits)
• Extreme proactivity and ownership: closes loops without reminders; drives tasks to completion; holds self and others accountable
• Comfort operating with senior customer stakeholders and senior engineers; confident presence in high-stakes rooms
• Strong judgment and composure under pressure; ability to make good decisions quickly with incomplete information
• Metrics-driven operator: owns and reviews delivery health KPIs weekly (e.g., on-time milestone rate, schedule variance, blocker aging, action item closure, risk hygiene, scope change rate, comms cadence/SLA, SSOT quality) and drives corrective actions until trends improve
• Delivery leadership: status, risk, scope, and dependency management; stabilizing slipping engagements
• Systems/process building with good taste: knows when to add structure vs. remove friction
• AI/automation mindset: identifies repetitive work and builds workflows to reduce overhead
• Client IT integration execution: access, procurement, VDI/VPN, tooling and permissions orchestration
• Clear communication across technical and non-technical audiences; influences without authority

Desirable

• Scale is accelerating the development of AI across the world's most important organizations. This role is the execution leader and operating-system builder that makes enterprise deployments succeed on the ground
• You will keep engagements on track, anticipate what customers and forward-deployed teams need before they ask, and remove every obstacle standing between the team and great work
• This is a combined scope role: you own delivery outcomes end-to-end (status, risk, blockers, stakeholder confidence) and you build the machine that runs deployments (SSOT, task systems, automation, client IT integration, logistics, reporting, and finance/compliance operations)
• Run the execution machine for each engagement: translate customer outcomes into OKRs, then into an integrated delivery plan (Gantt) with milestones, dependencies/critical path, DRIs, definitions of done, and change-control as scope shifts
• Keep delivery on track end-to-end: maintain crisp status, track variance vs plan, surface risks early, and drive blockers to resolution so engineers stay focused on technical work
• Own follow-through and accountability: run tight cadences to drive tasks to completion without reminders, ensure every open item has an owner + due date, and hold teams accountable to outcomes and deadlines
• Build durable delivery systems and stakeholder trust: create playbooks and tracking systems (SSOT, action item/risk registers, reporting) that reduce friction, and maintain trusted customer relationships through clear, proactive communication
• Maintain a flawless, easily accessible Single Source of Truth (SSOT) for all project artifacts so the team never has to search for information
• Bring the full power of AI to daily operations: identify bottlenecks and build tools, trackers, and AI-driven workflows to automate administrative overhead
• Spearhead seamless integration into client IT, data systems, and VDI/VPNs; coordinate device procurement and access in partnership with client stakeholders and Scale Corporate IT
• Own scheduling, onsite travel logistics, and meeting follow-through across time zones; capture action items and proactively drive progress to completion
• Own operational communications and reporting: draft regular (often daily) customer updates, monitor to unblock stalled threads, and deliver live/asynchronous reporting that provides transparent engagement health to customers and Enterprise/deployment leadership