Senior AI Engineer: Build Production AI Platforms (Remote)

UL Solutions

Warszawa

On-site

PLN 230,000 - 250,000

Full time

14 days+

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Benefits offered by this job

Annual bonus 10%

Flexible working arrangements

Access to ULS University

Two volunteering days per year

Annual paid leave

Job summary

UL Solutions seeks a Senior AI Engineer to design, deliver, and continuously improve scalable AI solutions that drive measurable business value. You will translate business needs into production-ready AI systems, lead cross-functional teams, and ensure secure, enterprise-grade software across cloud-native architectures.

The role emphasizes mentorship, collaboration, and adherence to UL Solutions Ways of Working.

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.
Ensure AI solutions adhere to security, privacy, governance, compliance, operational, and Responsible AI requirements.
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.