Sr Staff AIOps Engineer

GE HealthCares 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.

Were 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.

Core Responsibilities

• Develop and operationalize ML and GenAI pipelines to enable scalablereliable and secure deployment of AI models across GE HealthCares enterprise landscape

• Automate model lifecycle management including model versioning continuous integration (CI/CD) testing deployment observability and monitoring and governance in alignment with enterprise standards

• Partner with IT and cloud teams to optimize infrastructure for AI workloads across hybrid and multi-cloud environments (AWS Azure)

• Collaborate with cross-functional teams including data scientists software engineers architects and domain experts to ensure smooth end-to-end delivery of AI solutions

• Integrate Generative AI capabilities (e.g. LLMs multimodal models) into business workflows enhancing automation productivity and decision intelligence

• Conduct research and proof-of-concepts to evaluate emerging tools frameworks and architectures for GenAI and ML Ops ( Kubeflow MS CopilotOpenAiAgent Builder)

• Mentor and guide data science and engineering teams on best practices in productionizing AI models and managing their lifecycle

• Promote a culture of innovation collaboration and continuous improvement within the Enterprise AI team.

Experience & Qualifications Requirements

• PhD orMasters degree in Computer Science Data Science Engineering or a related discipline with a strong focus onengineering and ML/Dev Ops

• Advancedhands-on experience in developing deploying and maintaining ML/AI development pipelines and applications in enterprise environments

• Proficiency in Python cloud platforms (AWS Azure) containerization CI/CD and DevOps practices (Docker Kubernetes GitHub Actions Jenkins)

• Working knowledge ofMLOps /GenAIOpstools and frameworks ( SageMakerBedrock LangSmithLangGraph)

• Proven ability to translate research and prototypes into scalable enterprise-grade solutions

• Excellent communication collaboration and stakeholder management skills with the ability to influence both technical and executive audiences

• Curiosity and drive for continuous learning staying current with advances in GenAI MLOps and AI infrastructure technologies

• Experience with vector databases (e.g. Pinecone FAISS Milvus) and retrieval-augmented generation (RAG) pipelines

• Experience with LLM prompt engineering andLangChainarchitecture

• Strong understanding of multi-agent or distributed AI ecosystems enabling consistent model-to-model communication (MCP A2A) and orchestration.

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For Poland based positions Annual Salary Range:356000.00PLN-489500.00PLN

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.

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

Relocation Assistance Provided: No