AI Lead Engineer

Description

The company is setting up an AI Center of Competence to speed up engineering work, raise design quality and build smarter engineering tools across civil, mechanical, electrical, controls and software.

The AI Lead Engineer will define the direction, build the basics (governance, platforms and operating model) and deliver early AI pilots that give engineers and project teams real value.

This is a hands-on leadership role that needs technical depth, domain knowledge and strong work with stakeholders.

Your impact

Build the AI Center of Competence from scratch. Set its mission, operating model, governance and technical standards for responsible AI use. Form working relationships with IT, cybersecurity, legal and engineering leaders so AI can be deployed at scale, securely and in line with rules.

Show measurable productivity gains in engineering within the first year. Pick and run 2 to 3 high-impact pilots, such as automating engineering documentation, retrieving design knowledge or assisting with controls and code. Each should clearly cut cycle time, improve quality and free expert time.

Turn engineering problems into AI tools that can be deployed. Work directly with civil, mechanical, electrical, controls and software teams to learn their workflows, tools (PLM, CAD, ERP, document systems) and limits, then turn real problems into practical AI applications with high value.

Prepare AI-ready data for long-term use. Make engineering data structured, governed and easy to find by improving data ownership, metadata standards, lineage tracking and access control. This lays the base for knowledge graphs and intelligent agents.

Connect strategy with delivery in industrial AI. Advise engineering leaders on AI opportunities, risks and return on investment, while personally prototyping, testing and rolling out solutions in enterprise settings.

Plan what comes after the first pilots, including AI-assisted design reviews, engineering copilots and knowledge systems that span disciplines.

Your background

Solid experience in applied AI and machine learning.

Proven record of designing and deploying AI in enterprise settings, especially in generative AI, LLMs, NLP and document intelligence.

Experience building production-grade AI systems and handling the full lifecycle, including data pipelines, model development, MLOps and deployment on modern cloud platforms.

Some exposure to engineering-heavy fields such as power systems, mechanical, electrical, controls, automation or similar industrial work.

Experience with complex engineering data and systems such as PLM, ERP, CAD/CAE, requirements management or large document management environments.

Track record of working across engineering, IT and leadership, and explaining AI ideas in plain terms to people outside AI.

Comfortable with ambiguity, building new capabilities from zero, shaping strategy and driving adoption of new technology across teams.

Responsibilities

• Build the AI Center of Competence from scratch, including its mission, operating model, governance and technical standards for responsible AI.
• Build working relationships with IT, cybersecurity, legal and engineering leaders to make AI deployment scalable, secure and compliant.
• Pick and run 2 to 3 high-impact AI pilots, such as engineering documentation automation, design knowledge retrieval or controls and code assistance, that deliver measurable productivity gains within the first year.
• Learn the workflows, tools (PLM, CAD, ERP, document systems) and constraints of civil, mechanical, electrical, controls and software teams, and turn their problems into deployable AI solutions.
• Make engineering data structured, governed and discoverable by improving data ownership, metadata standards, lineage tracking and access control.
• Advise engineering leadership on AI opportunities, risks and return on investment, and personally prototype, test and deploy solutions.
• Plan the roadmap beyond the first pilots, including AI-assisted design reviews, engineering copilots and cross-discipline knowledge systems.

Requirements

• Strong expertise in applied AI and machine learning.
• Proven experience designing and deploying AI solutions in enterprise environments, with particular depth in generative AI, LLMs, NLP and document intelligence.
• Experience building production-grade AI systems across the full lifecycle, including data pipelines, model development, MLOps and deployment on modern cloud platforms.
• Exposure to engineering-heavy domains such as power systems, mechanical, electrical, controls or automation.
• Experience with complex engineering systems and data, such as PLM, ERP, CAD/CAE, requirements management or large document management environments.
• Ability to work across engineering, IT and leadership teams and explain AI concepts in practical terms to non-specialists.
• Comfort with ambiguity, building new capabilities from zero and driving adoption of emerging technology.

Conditions

Location: Västerås, Västmanland County, Sweden.

Full-time position.

Not remote.

Application reviews happen on an ongoing basis.

Recruiting questions go to Recruiting Manager Kyle Chan, with Talent Acquisition Partner Fredrik Söder for other questions.

Accessibility assistance in the application process is available only to job seekers with disabilities.

Pre-employment background checks are carried out in line with applicable law and may include employment, education and criminal record verification.

Some roles may require more extensive background or security screening, which will be explained and require consent before it starts.

Benefits

• Covered by a collective agreement.
• Flexible working hours.
• Health care and wellness allowance.
• Career opportunities within the company in Sweden and globally.
• A mentor to support you through onboarding.
• Training and education to support your development.
• Team members from more than 70 nationalities in Sweden.
• Supplementary pay during parental leave.
• Employee benefit portal with thousands of discounts and perks.