Senior Technical Project Manager (Region Delivery)

An overview of this role

As an AI Transformation Owner at GitLab, you'll shape your function's AI strategy and build the solutions that deliver it. You are the person responsible for identifying where AI can fundamentally change how your org operates, partnering with your Executive Sponsor to align on the biggest challenges, and driving measurable outcomes against them.

Think of this as a product management role where the product is your org's way of working. You'll manage the full lifecycle: understanding how work flows today, deciding where AI should reshape it, prioritizing what gets built and in what order, and ensuring what ships actually gets adopted. You'll also prototype solutions, configure agents, and prove what's possible before pulling in engineering support to scale it.

You will work closely with an AI Engineer who sits within the Enterprise AI team. Together you form a partnership: you bring the business context, process intelligence, and strategic prioritization. They bring the technical depth, production-grade delivery, and architecture decisions. You'll build working solutions at the no-code and low-code layer, and partner with the AI Engineer on the right approach, tooling, and structure.

What you'll do

Strategy & Prioritization

• Own your function's AI strategy, aligned with your Executive Sponsor and business priorities. Understand which metrics matter to the org, identify what will move the needle, define how you'll measure impact, and track progress over time.
• Map how work flows across your function end-to-end, including the handoffs upstream and downstream to other orgs. Identify where the real constraints are, not just the ones your team can see. Focus on the 100x problems: where could leveraging AI in a workflow let your org execute it orders of magnitude faster, or at 100x more volume than before?
• Manage intake of AI requests, ideas, and pain points from across the function, including via your Champion network. Ensure every team member has a clear route to surface what they need, rather than building independently.
• Prioritize strategically against business outcomes and executive guidance. Hold the line on priorities - we cannot change direction every two weeks - and ensure the AI Engineer's time is spent on the highest-impact work.

Adoption & Change Management

• Reimagine, not just automate. Challenge your org to think beyond injecting AI into existing workflows. Work with Enterprise AI to spot opportunities to fundamentally rethink how work gets done.
• Drive adoption and change management together with the AI Engineer. The best AI solution is worthless if nobody uses it. Create the channels, rituals, and feedback loops that make AI visible in your function: shared spaces for teams to show what they've built, regular office hours, onboarding for new hires, and celebration of wins. Own the rollout and iteration needed to make AI initiatives stick.
• Coordinate with Enterprise AI to ensure your function benefits from patterns, tools, and learnings emerging across other parts of the business.
• Build and bridge the Champion network in your function. Champions are the peer community that extends your reach beyond what you and the AI Engineer can deliver directly. From early in the role, identify and recruit Champions across sub-teams (5-10% time, formally agreed with their manager), run a regular Champion sync, host demos to the wider function, and act as their bridge to Enterprise AI. Champions are not your reports: you coordinate them, you don't manage them. Without this network, your reach is capped.

Hands-On Building & Agent Operations

• Build AI agents using no-code and low-code platforms (e.g. Glean, Workato, similar tools). Go from idea to working prototype without waiting for engineering.
• Author and iterate on skills files that define how AI agents behave. Refine instructions based on real usage and share reusable skills across the function.
• Configure MCP servers and tools, giving agents access to the business systems they need. Partner with the AI Engineer on what to connect and how to do it securely.
• Own your function's fleet of agents. Some agents will be used directly by people in your org. Those that aren't, you own. Either way, you're accountable for their performance: tracking KPIs, running evaluations after model or data changes, and iterating based on what you learn.
• Expect to rebuild. AI tools and models evolve fast. The agent you built last month may need to be replaced, not patched. You should be comfortable sunsetting your own work when a better approach emerges, and helping your org stay current rather than attached to what exists today.

What you'll bring

Business & Strategic

• Deep knowledge of your function's operations. You understand how work moves through your org, where it gets stuck, and why. You can trace a process end-to-end and explain how it connects to the teams around it.
• Strategic prioritization skills. You've managed competing demands before and can make hard calls about what matters most. You think in terms of business outcomes, not activity.
• A product management mindset. You naturally think about intake, backlog, iteration, and adoption. You're comfortable defining success metrics and holding yourself accountable to them.
• Strong communication and influence. You'll be the person saying "not yet" to some teams and "think bigger" to others. You need the credibility and interpersonal skills to make both of those conversations land.
• Cross-functional instincts. You default to understanding how your org's processes affect and are affected by the teams around you - not just optimising in isolation.
• Experience building peer networks or communities of practice. You've recruited and sustained volunteer contributors before, whether as a guild lead, champion program owner, or community organizer. You know how to motivate people whose time you don't directly own.

Hands-On & Technical

• Comfortable building with AI tools. You don't need to write production code, but you should be able to build a working agent, configure a skill, connect an MCP server, and troubleshoot when something isn't working. Think: power user, not software engineer.
• Ready to learn fast. Experience with or willingness to quickly pick up no-code/low-code AI platforms, prompt engineering, and agent configuration. You'll be trained on GitLab's specific tooling, but you should arrive ready to get your hands dirty.
• Strong conceptual understanding of AI capabilities - summarization, classification, generation, automation, agentic workflows - and a commitment to staying current. The landscape shifts constantly. The tools you use today may be obsolete in weeks. You stay on top of new developments so that your org's AI strategy reflects what's actually possible, not what was possible six months ago.
• Ability to map data flows - structured and unstructured. Understand where agents need context, and figure out where humans should interface with automated workflows and at what steps.

About the team

You will partner closely with Enterprise AI within the Enterprise Technology & AI organization, while remaining embedded in your own function. Enterprise AI provides the technical delivery capability, platforms, and patterns. You provide the business context, prioritization, building at the no-code layer, and adoption muscle. Together, you form the core of your function's AI transformation.

The role

We are looking for a structured, proactive, and technically strong Technical Program Manager to coordinate technical execution within our Post-Sales organization in the United States.

Nebius Post-Sales teams work with customers running production workloads on our cloud infrastructure. Your mission is to make this work predictable and scalable by maintaining clear execution plans, technical dependencies, ownership, customer health, and operational processes.

A key part of the role is the transition from Pre-Sales into Post-Sales. You will ensure that customer architecture, technical requirements, service dependencies, known risks, and operational context are carried into production with clear ownership. As customers move through production, you will maintain visibility into their health and core technical issues and coordinate dependencies across Post-Sales, Support, Product, and Engineering.

You will work closely with architects and engineers and develop a strong understanding of customer environments and Nebius cloud infrastructure. You should be able to translate technical requirements into execution plans, identify missing dependencies and readiness gaps, challenge incomplete plans, and coordinate technical work across several teams.

This role is remote within the United States and requires candidates to be based on the East Coast.

Your responsibilities will include: 

• Coordinate technical execution across US Post-Sales customers, maintaining clear plans, dependencies, risks, ownership, and status.

• Own and improve the Pre-Sales to Post-Sales transition, including customer architecture, technical requirements, dependencies, documentation, and ownership handover.

• Partner with architects and engineers to translate production requirements into execution plans and identify technical gaps or dependencies.

• Proactively identify weaknesses in Post-Sales processes and design, implement, and measure practical improvements.

• Build and maintain reporting on customer health, core technical issues, risks, blockers, team capacity, and Post-Sales initiatives.

• Own and continuously improve Jira boards, workflows, automation, dashboards, and reporting used for Post-Sales execution.

• Create and maintain processes, procedures, playbooks, templates, and technical and operational documentation

We expect you to have: 

• 5+ years of experience in technical program management, technical project management, technical delivery, or a related role.

• Strong understanding of cloud infrastructure, including compute, storage, networking, and production cloud environments.

• Strong technical fluency and the ability to understand customer architectures, system dependencies, technical constraints, and operational risks.

• Experience coordinating technically complex initiatives across Engineering, Product, architects, and other technical teams.

• Ability to translate technical requirements into structured execution plans and identify missing dependencies or readiness criteria.

• Ability to read, understand, and write technical documentation related to cloud infrastructure and customer environments.

• Advanced hands-on Jira experience, including boards, workflows, automation, dashboards, and reporting.

• Proven experience proactively identifying, designing, and implementing process improvements.

• Experience creating and maintaining processes, procedures, playbooks, templates, and operational documentation.

• Knowledge of change management practices and techniques.

• Fluent English.

It will be an added bonus if you have: 

• Experience with Post-Sales, Customer Engineering, Solutions Architecture, Professional Services, or Technical Support.

• Experience working with AI/ML infrastructure or GPU-based workloads.

• Familiarity with Kubernetes, workload schedulers, or large-scale compute environments.

• Knowledge of service delivery methodologies and frameworks such as PMI, ITIL, or Agile.

• Experience working in a globally distributed technology organization.

Key employee benefits in the US:

• Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan: Up to 4% company match with immediate vesting.
• Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote work reimbursement: Up to $85/month for mobile and internet.
• Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.

Nebius is looking for a Technical Program Manager to join our Capacity team and drive capacity expansion across our data centers.

In this role, you will work at the inersection of data analysis, infrastructure engineering, procurement, data center operations, and product teams. You will analyze how cloud resources are consumed, forecast future demand, identify capacity risks, and coordinate infrastructure expansions — from identifying the need for additional capacity to making that capacity available to customers.

The role covers several key cloud resources, including compute and storage capacity, ultimately translating demand forecasts into requirements for additional servers across our data centers.

This is a hands-on, analytical role. We are looking for someone who is comfortable working with metrics and forecasts and can use data to make decisions, while also being able to coordinate complex cross-functional projects involving multiple engineering and business teams.

Your responsibilities will include

• Analyze historical and current consumption of cloud resources and identify trends, anomalies, and potential capacity constraints.

• Build and maintain capacity forecasts for infrastructure resources and translate them into concrete capacity requirements across multiple data centers.

• Initiate capacity requests and work with Supply Chain teams throughout the purchasing and delivery process.

• Maintain a clear end-to-end view of capacity expansions, from forecast and capacity requirements through procurement, delivery, installation, deployment, and availability for customers.

• Coordinate expansion plans with data center teams, including installation schedules and infrastructure readiness.

• Coordinate with engineering teams to plan deployment of new capacity.

• Provide engineering, product, and business stakeholders with clear and reliable information about capacity plans, delivery timelines, current status, dependencies, and risks.

We expect you to have:

• Have experience in technical project/program management, data analytics, capacity planning, infrastructure planning, or a similar role.

• Have a strong analytical background and be comfortable making decisions based on quantitative data.

• Understand basic statistical concepts and forecasting methods and know their practical limitations.

• Be comfortable communicating with infrastructure engineers and understanding technical constraints and dependencies.

• Be able to coordinate work across multiple independent teams without relying on direct authority.

• Have strong written and verbal communication skills and be able to translate technical and analytical information into clear plans, decisions, risks, and status updates for different audiences.

• Take ownership of outcomes: proactively identify upcoming problems, drive decisions, follow up on commitments, and ensure that issues do not disappear between teams.

It would be a strong advantage if you have:

• Have worked as a data or product analyst before moving into project or program management.

• Can independently query data using SQL.

• Have hands-on experience with monitoring and BI tools such as Grafana, DataLens, or similar platforms.

• Have experience with capacity planning, demand forecasting, or infrastructure resource management.

• Understand the basic architecture of cloud or data center infrastructure, including servers, racks, compute, storage, networking, and their operational dependencies.

• Have experience working with procurement, hardware supply chains, or physical infrastructure deployments.