AI Engineer

Job description

Company Description 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.

Job Description

In AECOM’s AI Engineering team your code will directly shape the physical world around us. We build AI-driven technology that revolutionises how infrastructure and buildings are designed and engineered; reducing waste, cutting CO₂, and making the built environment more efficient and sustainable. This is where software has measurable, real-world impact. With our AI Engineering team we’ve created a unique setup: a lean, highly technical team with the speed and ownership of a start up, backed by the scale, resources, and domain expertise of one of the world’s leading engineering firms.

We are leading the industry’s AI transformation, and with our people and technology we deliver excellence and innovate with impact. We invite you to bring your bold ideas and big dreams to solve the world’s most complex challenges. Join us.

What You’ll Do

As part of the Assurance & Insight team, you will focus on designing, implementing and deploying LLM based solutions into production.

• Using various LLM models with latest approaches (agentic, context engineering) to solve challenging problems

Work end-to-end on ML solutions

• from data preparation and evaluation, deployment, and monitoring
• Develop text representation and semantic extraction pipelines for structured knowledge from unstructured data
• Collaborate with product teams and domain experts to integrate LLM features into our SaaS platform

Qualifications Must-Have Qualifications

• Master’s degree in Computer Science, Data Science, Computational Linguistics, or related field
• Hands-on experience with LLM techniques for text representation and semantic data extraction
• Knowledge on best practices and Evaluation techniques
• Proven experience working end-to-end on Software solutions and CI/CD Pipelines
• Proficiency in Python and pydantic validation
• Experience building RAG systems, Prompt engineering, Data processing

Preferred Skills

• Understanding of optimizing both CPU-bound and GPU-bound workloads.
• Knowledge of monitoring and observability tools (e.g. Prometheus, Grafana, Elastic stack).
• Experience with Infrastructure as Code (Terraform).
• Experience with Azure
• Experience with Machine Learning
• Experience in building product for the construction industry. Additional Information Our Hiring Process + 25-minute screening call

Take-home challenge

• A hands-on task to assess your problem-solving and technical skills
• Combined technical and cultural interview (in-person)

Whiteboard Interview

• 1-hour with 2 of our engineers to discuss your solution to the take-home challenge (60 min)

Culture fit

• In-person meeting with our leadership team (30 min) Why Join Us?
• Work on real-world problems where AI creates measurable impact.
• Be part of a team where your work matters, and your ideas become real.
• Collaborate with sharp, driven colleagues in a culture of trust, ownership, and high standards.
• Contribute to making the built environment smarter and more sustainable.

ReqID

J10158116

Business Line

Corporate

Business Group

Corporate

Strategic Business Unit

AI Engineering

Career Area

Information Technology

Work Location Model

On-Site