AI Product Manager - Transportation

AECOM is recruiting an AI Product Manager for Transportation to own the direction and delivery of AI products for transportation infrastructure. The role leads a small, highly technical team from problem definition through to deployed product, working on AI, simulation and optimisation applied to transportation engineering. The products are intended for use by engineers on real projects.

Responsibilities

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 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 such as 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

Requirements

A deep desire to challenge and change the way transportation engineering is done today; 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

Nice to have

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 geospatial analysis; Experience working with stochastic or probabilistic approaches to engineering and decision-making

Benefits

Medical, dental, vision, life, AD&D and disability benefits; Paid time off; Leaves of absence; Voluntary benefits; Perks; Flexible work options; Well-being resources; Employee assistance program; Business travel insurance; Service recognition awards; Retirement savings plan; Employee stock purchase plan; Award-winning training and development programs