Senior Project Manager

What Cognite is: Relentless to achieve

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

About the Role

As a Deployment Strategist, you are the owner of the customer's problem and the value we promise to deliver. You are the bridge between a customer's business objective and our technical delivery team, accountable for the "why" and the "what", while Solution Architects and Data Engineers own the "how".

You will work with senior customer stakeholders to scope value, define pilots and releases, steer delivery through to go-live, and drive adoption so that value is actually realized after launch. You combine the discipline of a program manager with the product thinking of a field product owner, and you are as comfortable in a steering committee as you are in a working session with plant engineers.

This is a hands-on role. You are expected to shape the engagement, not just report on it.

What You'll Do

Scope and define value

• Partner with Revenue to run discovery, map stakeholders, and translate business problems into a clearly scoped engagement (outcomes, MVP, success criteria, timeline, commercial boundaries).
• Build value cases and success metrics with the customer, and keep them visible throughout delivery.
• Define what "done" and "valuable" mean for each release, and manage scope against them.

Own delivery outcomes

• Lead engagements end to end, from kickoff through go-live, using an iterative, continuous-delivery approach.
• Prioritize the backlog with the customer and the delivery team, and make trade-off decisions on scope, timeline, and quality.
• Manage risk, dependencies, and escalations across customer, partner, and internal teams, and unblock technical and political issues early.
• Own delivery health: plan, margin, forecast, resourcing needs, and status reporting.

Drive adoption and value realization

• Own the path from go-live to measurable usage: adoption plans, enablement and training, user feedback loops, and health indicators.
• Identify blockers to adoption and expansion signals early, and act on them with the account team.
• Prepare a clean handoff to the long-term run and support model.

Lead with partners and the team

• Coordinate delivery with system integrator and partner teams, and protect clear accountability and contract boundaries.
• Guide Solution Architects, Data Engineers, and Data Scientists in the engagement, and coach junior colleagues.
• Contribute to the Value Delivery playbook: lessons learned, reusable templates, and delivery standards.

Feed the product

• Turn field insight into structured product feedback for Product and Engineering.
• Use AI tooling in your own work (analysis, documentation, reporting, prototyping) and help the team raise its standard.

What You Bring

Must have

• 5+ years of experience in customer-facing delivery, program management or technical advisory for enterprise software or data/AI platforms.
• A track record of owning complex, ambiguous engagements through to measurable customer outcomes.
• Comfort with technical subject matter (data platforms, integration, cloud, analytics, or AI/ML). You do not need to build the solution, but you must understand it well enough to scope it and challenge it.
• Executive-level communication: you can present, negotiate, and make decisions with senior customer stakeholders and with delivery engineers on the same day.
• Strong command of agile and iterative delivery, backlog prioritisation, and scope management.
• Fluent English and ideally French
• Willingness to travel to customer sites up to 50%.

Nice to have

• Experience in industrial sectors (energy, oil and gas, chemicals, pharma, manufacturing, utilities).
• Experience with value-based scoping (ROI/TCO) and authoring product requirements or solution specifications.
• Experience working in multi-vendor delivery models with system integrators.
• Exposure to industrial data, knowledge graphs, or operational technology environments.
• Experience in a high-growth software company or a "builder" role in a startup.