Senior Software Engineer in Zug

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.

Our innovation hubs in London, Oslo and Zug bring different perspectives, disciplines, and ways of thinking into the same room, because the hardest engineering problems demand it.

The role is a full-time, on-site position based in Zug, Switzerland.

Qualifications

As a Senior Software Engineer, you’ll build the production software that powers AECOM’s AI-driven engineering products, working across backend systems, platform engineering and machine learning systems.

Strong software engineering fundamentals, ownership of meaningful production systems and depth in one area matter more than matching every technology in our stack.

You’ll design and build backend services, APIs and data flows; evolve system architecture; and make sound trade-offs in areas such as database design, schema evolution, scalability and performance.

You’ll own substantial work from problem definition and design through implementation, deployment and ongoing production support, improving reliability and resolving difficult issues along the way.

Working closely with software and ML engineers, product teams and engineering-domain experts, you’ll help turn research into reliable, production-ready tools.

Depending on your background, this may include integrating models into products, building deployment and monitoring capabilities, or optimising AI workloads.

Previous professional AI/ML experience is valuable, but is not required for every hire.

• Must-Have Qualifications
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Strong hands-on Python programming skills and experience building production backend services, APIs or other substantial software applications.

Familiarity with frameworks such as Fast API, Flask or Django is useful.

• Demonstrated ownership of technically challenging production systems, from design and implementation through deployment and ongoing improvement.

You can explain your personal contribution, key decisions and the outcomes delivered.

• Strong system design and engineering judgement, with experience making practical trade-offs around architecture, data models, reliability, scalability or performance, and diagnosing difficult production problems.
• Strong communication and collaboration skills, with the ability to turn loosely defined problems into practical solutions and drive delivery with limited direction in a lean team.
• Sound software development practices, including automated testing, code review, version control and CI/CD, with a focus on maintainable code and reliable production delivery.
• Preferred Skills
• Experience bringing AI/ML capabilities into production, such as model deployment and monitoring, ML pipelines, model serving, or LLM-powered applications and retrieval-augmented generation (RAG).
• Cloud and platform engineering experience with AWS, Azure or GCP; Docker or Kubernetes; Infrastructure as Code such as Terraform; or deployment pipelines such as Git Hub Actions.
• Depth in distributed or event-driven systems, asynchronous processing, or data-intensive and high-throughput applications.
• Experience with observability and performance tuning, including tools such as Prometheus, Grafana, ELK or Datadog, or optimising CPU-, GPU- or distributed ML workloads.
• Experience in startups, scaleups or greenfield product development; or familiarity with engineering software, simulation, optimisation or building design automation.
• 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
• Whiteboard Interview: 1-hour with 2 of our engineers to discuss your solution to the take-home challenge
• Culture fit: 30-minute meeting with our leadership team

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.
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