Senior AI Engineer

UL Solutions; Poland; Hybrid; PLN 230,000 - 250,000; Full time

Benefits offered by this job

Annual bonus 10%

Annual paid leave

ULS University access

Volunteer days

Flexible working arrangements

Job summary

UL Solutions is seeking a Senior AI Engineer to deliver scalable AI solutions and drive MLOps-powered platforms. You will own end-to-end AI initiatives, collaborating with product, engineering, and business teams to ensure measurable outcomes and enterprise-grade implementations.

The role emphasizes security, governance, and responsible AI, with flexible work arrangements including hybrid or remote work from offices in Dublin, Barcelona or Warsaw.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Data Analytics, or a related field.
• 5+ years of experience developing software, AI, machine learning, cloud, or data-driven solutions.
• Strong Python software engineering experience using modern development practices.
• Experience designing and delivering scalable, secure, and maintainable software and AI solutions.
• Experience building and deploying AI and machine learning solutions into production.
• Experience with cloud platforms, preferably Microsoft Azure.
• Experience with Azure DevOps, CI/CD, Infrastructure as Code (IaC), MLOps, and deployment automation.
• Experience developing distributed systems, APIs, and enterprise integrations.
• Experience with Docker, Kubernetes (K8s), and containerized application deployment.
• Experience with LLMs, RAG, document intelligence, intelligent automation, or related AI technologies.
• Strong understanding of software architecture, engineering best practices, and enterprise security considerations.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Demonstrated ability to lead technical initiatives and work effectively in Agile environments.

Responsibilities

• Lead the design, delivery, and continuous improvement of scalable AI solutions, products, frameworks, and capabilities that deliver measurable business value.
• Translate business needs into production-ready AI systems and enterprise integrations with clear outcomes and success metrics.
• Develop and implement AI solutions using LLMs, RAG, agentic frameworks, document intelligence, machine learning, and data science techniques.
• Evaluate and apply appropriate AI technologies, patterns, and tools to maximize business impact and maintainability.
• Design, develop, and maintain scalable, cloud-native, and enterprise-grade applications using modern software engineering practices, clean architecture, reusable design patterns, and comprehensive testing.
• Define and evolve engineering standards, frameworks, and reference architectures while providing technical leadership on solution design, architecture decisions, and engineering best practices.
• Design, deploy, and operate scalable AI platforms and solutions on Azure using modern DevOps and MLOps practices, including CI/CD, Infrastructure as Code (IaC), containerization, automation, and cloud-native architectures.
• Manage the full lifecycle of AI applications, platforms, and models, including deployment, monitoring, observability, performance optimization, reliability, release management, and operational support.
• Implement and maintain secure, resilient, and observable production environments through monitoring, logging, alerting, governance, and infrastructure best practices.
• Design and execute testing, evaluation, and experimentation strategies to validate solution effectiveness and business value.
• Continuously improve AI solutions through performance measurement, monitoring, feedback, and iterative optimization.
• Collaborate with product, engineering, platform, and business teams to deliver AI solutions aligned with organizational objectives and measurable business outcomes.
• Communicate technical concepts effectively, provide technical leadership and mentorship, and influence solution direction through collaboration and engineering best practices.
• Demonstrate strong ownership, accountability, adaptability, and commitment to UL Solutions Ways of Working while fostering a culture of trust, innovation, continuous learning, and continuous improvement.

Skills

Python

Cloud platforms (Azure)

DevOps / MLOps

CI/CD

APIs / distributed systems

Kubernetes

LLMs / AI tech

Security / governance

Agile

Education

Bachelor's degree in CS / SE / Data Science

Master's degree preferred

Tools

Azure DevOps

IaC

Docker

Kubernetes

Job description

The Senior AI Engineer is responsible for delivering business value through the design, delivery, and continuous improvement of AI solutions that support core business functions. This role focuses on applying advanced AI engineering techniques, tools, platforms, software engineering, architecture, and MLOps practices to develop scalable, production-ready systems that solve real business problems and contribute to long-term AI Labs capability growth.

As a highly collaborative and delivery-focused senior individual contributor, you will own long-term, multi-person initiatives, including products, frameworks, and technical capabilities, ensuring work is clearly planned, measurable, and aligned to department value. You will work closely with product teams, engineering teams, business stakeholders, and platform consumers to translate business needs into scalable AI solutions, deliver measurable impact, and help others deliver successfully. You will balance technical excellence with strong ways of working, contributing to a culture of accountability, trust, mentorship, and continuous improvement.

This role requires deep applied AI engineering expertise across architecture, software engineering, experimentation, and MLOps, combined with the ability to communicate effectively, mentor others, influence technical direction, communicate trade-offs, and drive business-aligned outcomes through collaboration and leadership

We offer flexibility in how and where you work. This position can be based remotely or in a hybrid model from one of our offices in Dublin (Ireland), Barcelona (Spain), or Warsaw (Poland).

Responsibilities

AI Solution Delivery & Ownership

• Lead the design, delivery, and continuous improvement of scalable AI solutions, products, frameworks, and capabilities that deliver measurable business value.
• Translate business needs into production-ready AI systems and enterprise integrations with clear outcomes and success metrics.
• Develop and implement AI solutions using LLMs, RAG, agentic frameworks, document intelligence, machine learning, and data science techniques.
• Evaluate and apply appropriate AI technologies, patterns, and tools to maximize business impact and maintainability.

Software Engineering & Architecture

• Design, develop, and maintain scalable, cloud-native, and enterprise-grade applications using modern software engineering practices, clean architecture, reusable design patterns, and comprehensive testing.
• Define and evolve engineering standards, frameworks, and reference architectures while providing technical leadership on solution design, architecture decisions, and engineering best practices.

Cloud, DevOps & MLOps

• Design, deploy, and operate scalable AI platforms and solutions on Azure using modern DevOps and MLOps practices, including CI/CD, Infrastructure as Code (IaC), containerization, automation, and cloud-native architectures.
• Manage the full lifecycle of AI applications, platforms, and models, including deployment, monitoring, observability, performance optimization, reliability, release management, and operational support.
• Implement and maintain secure, resilient, and observable production environments through monitoring, logging, alerting, governance, and infrastructure best practices.
• Design and execute testing, evaluation, and experimentation strategies to validate solution effectiveness and business value.
• Continuously improve AI solutions through performance measurement, monitoring, feedback, and iterative optimization.

Governance, Security & Responsible AI

• Ensure AI solutions adhere to security, privacy, governance, compliance, operational, and Responsible AI requirements.
• Design solutions that are secure, reliable, scalable, and aligned with enterprise standards.

Collaboration, Leadership & Ways of Working

• Collaborate with product, engineering, platform, and business teams to deliver AI solutions aligned with organizational objectives and measurable business outcomes.
• Communicate technical concepts effectively, provide technical leadership and mentorship, and influence solution direction through collaboration and engineering best practices.
• Demonstrate strong ownership, accountability, adaptability, and commitment to UL Solutions Ways of Working while fostering a culture of trust, innovation, continuous learning, and continuous improvement.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Data Analytics, or a related field.
• 5+ years of experience developing software, AI, machine learning, cloud, or data-driven solutions.
• Strong Python software engineering experience using modern development practices.
• Experience designing and delivering scalable, secure, and maintainable software and AI solutions.
• Experience building and deploying AI and machine learning solutions into production.
• Experience with cloud platforms, preferably Microsoft Azure.
• Experience with Azure DevOps, CI/CD, Infrastructure as Code (IaC), MLOps, and deployment automation.
• Experience developing distributed systems, APIs, and enterprise integrations.
• Experience with Docker, Kubernetes (K8s), and containerized application deployment.
• Experience with LLMs, RAG, document intelligence, intelligent automation, or related AI technologies.
• Strong understanding of software architecture, engineering best practices, and enterprise security considerations.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Demonstrated ability to lead technical initiatives and work effectively in Agile environments.

Preferred Qualifications

• Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related discipline.
• Experience with generative AI technologies, including LLMs, RAG, agentic AI, and document intelligence solutions.
• Experience implementing AI evaluation, experimentation, and performance measurement frameworks.
• Experience mentoring engineers and providing technical leadership.
• Knowledge of responsible AI, governance, compliance, and security best practices.

Total Rewards: We understand that compensation is an important consideration as you plan your next career move. The salary range for this position in Poland is PLN 230,000 to 250,000, and is determined based on multiple factors, including job-related skills, experience, and qualifications. While this represents the typical range for the role, we may offer a higher salary for candidates with exceptional experience or expertise. We encourage you to discuss your expectations further with the recruiter and learn more. In addition to base salary, this position is eligible for an annual bonus with a target payout of 10% of base salary. You'll also benefit from annual paid leave, access to ULS University to support continuous learning and career growth, two volunteering days per year for community engagement, and flexible working arrangements to support work-life balance.

Disclaimer: This role is gender-neutral and open to all qualified applicants, regardless of gender identity or expression.

About Us

A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. UL ... The hidden text truncated