Senior Staff AIOps Engineer

Job Description Summary

GE HealthCare’s Chief Data and Analytics Office (CDAO) delivers innovative data, insights, and AI solutions across the organization. Our Enterprise AI team drives a diverse portfolio of Machine Learning (ML), Artificial Intelligence (AI), and Generative AI (GenAI) initiatives by combining agile execution with industry-leading methods and tools.

We're seeking a highly skilled and motivated Engineer experienced in ML and GenAI operations, software development, and AI architecture to join our dynamic and growing team.

As a Sr Staff AIOps Engineer, you will be at the forefront of operationalizing advanced Machine Learning and Generative AI solutions. You will design, deliver, and maintain robust development and deployment pipelines for high-impact AI applications across key business domains within GE HealthCare — including Finance, Commercial, Supply Chain, Quality, Operational Excellence, Lean, and Manufacturing.

Job Description

Core Responsibilities 

• Leading the design and operation of secure, reliable, and scalable platforms for deploying and managing AI/ML workloads across GE HealthCare.
• Defining and drive the AI/ML platform and MLOps roadmap, with a strong focus on AWS infrastructure, automation, standardization, and operational excellence.
• Establishing and improving CI/CD and MLOps practices across the model lifecycle, including testing, versioning, deployment, rollback, monitoring, and governance.
• Building and maintaining cloud infrastructure for AI/ML workloads using AWS services such as SageMaker, EKS, S3, IAM, and CloudWatch.
• Promoting infrastructure as code and repeatable environment management using tools such as Terraform or AWS CDK.
• Improving platform reliability, scalability, security, and cost efficiency in partnership with cloud, cybersecurity, architecture, and IT teams.
• Set standards for containerization, orchestration, deployment automation, observability, incident response, and production support.
• Working closely with data science, software engineering, and business teams to turn model prototypes into maintainable, production-ready services.
• Providing technical leadership and mentorship to engineers and data scientists adopting platform and DevOps best practices.
• Evaluating tools and approaches that improve AI/ML platform operations; support GenAI workloads where they fit business needs and enterprise standards.

Experience & Qualifications Requirements

• Master’s or PhD degree 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 services such as SageMaker, EKS, S3, IAM, and CloudWatch.
• Proficiency in Python and experience with infrastructure as code, preferably Terraform or AWS CDK.
• Practical experience with Docker, Kubernetes, CI/CD tools such as GitHub Actions or Jenkins, and Git-based development workflows.
• Experience designing production systems with a 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 skills, including the ability to work with technical teams and senior leaders.
• Experience supporting regulated or security-conscious enterprise environments is an advantage.
• Familiarity with Azure or hybrid cloud environments is a plus.
• Exposure to GenAI services and patterns, such as Amazon Bedrock or retrieval-augmented generation, is beneficial but not the primary focus of the role.

#LI-MT1

#LI-Hybrid

Pay Range

For Poland based positions, Annual Salary Range:356,000.00PLN-489,500.00PLN

Placement within this range depends on:

• Relevant skills and qualifications

• Prior job-related experience

• Internal equity considerations (alignment with colleagues in similar roles) e.t.c.

We review pay ranges regularly to ensure they remain competitive with the external market and align with our internal equity considerations.

Benefits & Rewards

In addition to base salary, our employees have access to a comprehensive package of benefits and allowances, which may include:

• Health & wellness coverage

• Retirement and or savings plans

• Allowances or benefits to support role requirements (e.g., mobility, transport, or role-specific needs such as a company car or allowance where applicable)

• Work-life balance support (e.g., flexible working, leave programs)

• Recognition and incentive programs aligned with performance and company success

The exact benefits package depends on the role, location, and employment terms as specified in the Colleague Value Proposition document that will be shared prior to the interview or at the offer discussion stage.

• Performance Bonus: Details to be shared during offer discussions

Additional Information

Relocation Assistance Provided: No