AI Product Manager - Transportation

AECOM · London, HOLBEIN GARDENS, United Kingdom

  • Senior
  • Full-time
  • Posted 2026-09-24
  • Confirmed live on 25 September 2026

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Job description

Job Description
AI for Engineering
We are building AI that changes how infrastructure is planned, designed and engineered.
Our starting point is simple: reality is stochastic, but engineering answers have traditionally been deterministic. That is one reason infrastructure is expensive.
Ground conditions, weather, loads, traffic, demand and prices are distributions. Treating them as single numbers does not remove uncertainty — it hides it. Historically, engineering has compensated by adding conservative margins and designing around worst-case assumptions.
We believe there is a better way.
By combining AI, simulation, optimisation and engineering expertise, we can expose the uncertainty that is already there and engineer against it. Instead of simply adding material to be safe, we can optimise designs against an explicit level of confidence.
We can explore dozens or hundreds of compliant solutions rather than two or three. We can make cost, carbon, performance and risk visible from the beginning of a project. And instead of disciplines working sequentially in a relay race, we can increasingly allow them to design concurrently against one live model.
The ambition is significant: better engineering decisions, dramatically faster design cycles, lower cost and materially more efficient infrastructure.
For our clients, that means lower cost and greater cost certainty; more design options earlier; explicit visibility of risk and confidence at every milestone; and the potential to remove 10–20% of material — and potentially cost — from a design while maintaining engineered confidence.
Transportation
Transportation is one of the most exciting areas for this approach.
Traffic, demand, network behaviour, construction constraints, land, cost and environmental conditions are inherently variable. AI gives us the opportunity to reason across those variables at a scale that would be impossible manually — and to help engineers and planners evaluate far more alternatives, much earlier.
As an AI Product Manager you will decide where that capability creates the most value for our clients and turn it into products that can be used on real projects. This is not a role focused on adding AI to existing workflows for the sake of it. We build what is useful to our clients and to the world.
You will work at the intersection of transportation engineering, AI, optimisation, data science and software engineering, leading a small, highly technical team from problem definition through to deployed product.
What You’ll Do
You will own the direction and delivery of AI products for transportation, working closely with engineers, planners, ML/RL researchers and software engineers.
You will:

• Own and evolve the product roadmap for AI-enabled transportation solutions, prioritising the problems with the greatest client and engineering value.

• Spend time with transportation teams and clients to understand where cost, time, uncertainty and engineering effort are concentrated today.

• Translate deep transportation-domain knowledge into technically grounded product requirements that ML/RL researchers and software engineers can build against.

• Lead ML/RL and software engineering teams to deliver working capabilities against clear milestones.

• Develop products that allow engineers to explore and compare large solution spaces across cost, carbon, risk, constructability and performance.

• Define how uncertainty, confidence levels and trade-offs should be represented so outputs remain useful and defensible in real engineering decisions.

• Define success through measurable outcomes: better designs, faster delivery, lower cost, reduced material, improved certainty and adoption on live projects.

• Test products on real transportation projects and use feedback from engineers and clients to iterate quickly.

• Represent the Transportation AI roadmap in discussions with market, technical, digital and executive leadership.

• Help move successful capabilities from prototypes into robust, repeatable products that can be deployed across AECOM globally.

Qualifications
Must-Have Qualifications

• A deep desire to challenge and change the way transportation engineering is done today. You should be motivated by rethinking the existing process, not simply digitising or automating it.

• Experience in transportation infrastructure, including planning, design, engineering, modelling or network analysis.

• Technical fluency in modern AI/ML approaches sufficient to work credibly with ML/RL researchers, data scientists and software engineers.

• Strong understanding of how engineering decisions are made, including constraints, uncertainty, trade-offs and validation.

• Ability to translate domain expertise and user needs into requirements technical teams can build against.

• Experience working across technical, engineering, client and executive audiences.

• Strong communication skills and the ability to make clear decisions across client value, scope, speed a

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