AI Engineer

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.  There has never been a better time to be at AECOM. 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. We're one global team driven by our common purpose to deliver a better world. 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 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.