AI Product Manager - Transportation

Work with Us. Change the World.

At AECOM, we're delivering a better world. Whether improving your commute, keeping the lights on, providing access to clean water, or transforming skylines, our work helps people and communities thrive. We are the world's trusted infrastructure consulting firm, partnering with clients to solve the world's most complex challenges and build legacies for future generations.

There has never been a better time to be at AECOM. With accelerating infrastructure investment worldwide, our services are in great demand. We invite you to bring your bold ideas and big dreams and become part of a global team of over 50,000 planners, designers, engineers, scientists, digital innovators, program and construction managers and other professionals delivering projects that create a positive and tangible impact around the world.

We're one global team driven by our common purpose to deliver a better world. Join us.

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.

• 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.

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 and technical feasibility.

Preferred Skills

• Demonstrated ownership of a product or technical roadmap, including prioritisation, stakeholder alignment and measurable outcomes.
• Experience in product management, technology delivery, technical leadership or a comparable role where you have taken a complex problem from concept through to adoption.
• Background in civil engineering, transportation engineering, transport planning or a closely related discipline.
• Experience with traffic modelling, network planning, corridor design, transport simulation or infrastructure optimisation.
• Hands-on exposure to reinforcement learning, optimisation, probabilistic methods, simulation or other advanced ML techniques.
• Experience with GenAI or LLM-based products applied to engineering, planning, simulation or design workflows.
• Familiarity with GIS, BIM, transport models, network data or...