Sr Staff AIOps Engineer

Description

The company's Chief Data and Analytics Office builds data, insight and AI solutions across the business. Its Enterprise AI team runs machine learning, AI and generative AI projects, combining agile delivery with proven methods and tools.

The company wants an engineer with experience in ML and GenAI operations, software development and AI architecture for this Sr Staff AIOps Engineer role.

You will help move advanced ML and GenAI solutions into production, building pipelines for high-impact AI applications in Finance, Commercial, Supply Chain, Quality, Operational Excellence, Lean and Manufacturing.

Responsibilities

• Lead the design and running of secure, reliable, scalable platforms that deploy and manage AI/ML workloads company-wide.
• Define and drive the AI/ML platform and MLOps roadmap, centred on AWS infrastructure, automation, standardisation and operational excellence.
• Build and improve CI/CD and MLOps practices across the model lifecycle, covering testing, versioning, deployment, rollback, monitoring and governance.
• Build and maintain cloud infrastructure for AI/ML workloads on AWS services such as SageMaker, EKS, S3, IAM and CloudWatch.
• Drive infrastructure as code and repeatable environment setup using Terraform or AWS CDK.
• Raise platform reliability, scalability, security and cost efficiency together with cloud, cybersecurity, architecture and IT teams.
• Set standards for containers, orchestration, deployment automation, observability, incident response and production support.
• Work with data science, software engineering and business teams to turn prototypes into maintainable, production-ready services.
• Mentor and lead engineers and data scientists as they adopt platform and DevOps practices.
• Assess tools and approaches that improve AI/ML platform operations, and support GenAI workloads where they suit business needs and enterprise standards.

Requirements

• A Master's or PhD in computer science, engineering, data science or a related field, or equivalent practical experience.
• Significant hands-on experience building and operating cloud platforms, DevOps pipelines or MLOps solutions in an enterprise environment.
• Strong AWS experience, including SageMaker, EKS, S3, IAM and CloudWatch.
• Python skills and experience with infrastructure as code, with Terraform or AWS CDK preferred.
• Practical experience with Docker, Kubernetes, CI/CD tools such as GitHub Actions or Jenkins, and Git-based workflows.
• A track record of designing production systems that focus on reliability, security, scalability, observability and cost management.
• Working knowledge of model lifecycle management and MLOps tools such as MLflow or SageMaker.
• Ability to lead technical initiatives, set engineering standards and mentor cross-functional teams.
• Strong communication and stakeholder management, including working with technical teams and senior leaders.
• Nice to have: experience supporting regulated or security-conscious enterprise environments is an advantage.
• Nice to have: familiarity with Azure or hybrid cloud environments is a plus.
• Nice to have: exposure to GenAI services and patterns such as Amazon Bedrock or retrieval-augmented generation is beneficial, though not the primary focus of the role.

Conditions

Hybrid work model.

For Poland-based positions, the annual salary range is 356,000.00 PLN to 489,500.00 PLN.

Where a person lands in the range depends on relevant skills and qualifications, prior job-related experience, and internal equity with colleagues in similar roles, and similar considerations.

Pay ranges are reviewed regularly to stay competitive with the external market and consistent with internal equity.

Benefits

• Beyond base salary, employees may have access to a broad package of benefits and allowances.
• Possible items include health and wellness coverage, retirement or savings plans, and allowances for role needs such as mobility, transport or a company car where applicable.
• Work-life balance support, such as flexible working and leave programs, and recognition and incentive programs tied to performance and company success.
• The exact package depends on role, location and employment terms, and is set out in the Colleague Value Proposition document shared before the interview or at the offer discussion.
• Performance bonus: details shared during offer discussions.
• Relocation assistance is not provided.