AI Engineer

Description

The AI for Engineering team builds AI technology that changes how infrastructure and buildings are designed and engineered, cutting waste and CO₂ and making the built environment more efficient and sustainable.

The team is small and highly technical, with the pace and ownership of a startup, backed by the resources and domain expertise of a leading engineering firm.

The company is a global infrastructure consultancy with over 50,000 planners, engineers, scientists, digital innovators and project managers, working in water, environment, energy, transportation and buildings.

Responsibilities

• As part of the Zug team, design, build and deploy LLM-based solutions into production.
• Apply a range of LLM models and current methods, including agentic systems and context engineering, to hard problems.
• Own ML work from data preparation and evaluation through deployment and monitoring.
• Build pipelines that extract text representations and structured knowledge from unstructured data.
• Work with product teams and domain experts to add LLM features to the company's SaaS platform.

Requirements

• A Master's degree in computer science, data science, computational linguistics or a related field.
• Hands-on experience with LLM techniques for text representation and semantic data extraction.
• Knowledge of evaluation techniques and good practice in applying them.
• A proven record of delivering software end-to-end, including CI/CD pipelines.
• Proficiency in Python and pydantic validation.
• Experience building RAG systems, prompt engineering and data processing.
• Preferred: understanding of tuning both CPU-bound and GPU-bound workloads.
• Preferred: knowledge of monitoring and observability tools such as Prometheus, Grafana and the Elastic stack.
• Preferred: experience with Infrastructure as Code using Terraform.
• Preferred: experience with Azure.
• Preferred: experience with machine learning.
• Preferred: experience building products for the construction industry.

Conditions

New hires must attend an in-person Day 1 onboarding at a company office as a condition of employment, as part of the company's commitment to a secure recruitment process.

The company is an equal opportunity employer and keeps all candidate information confidential under EEO guidelines.

Benefits

• Benefits depend on employment status and may include medical, dental and vision cover, life and AD&D insurance, disability cover, paid time off, leaves of absence, voluntary benefits, perks, flexible work options, well-being resources, an employee assistance program, business travel insurance, service recognition awards, a retirement savings plan and an employee stock purchase plan.
• Training and development programs to build your technical and leadership skills.
• Work on projects in your local community and worldwide, with access to cutting-edge technology and a network of experts.
• A respectful, collaborative workplace where you can grow.