Sr Staff AIOps and DevOps Engineer

I00929 GE Medical Systems Polska Sp. z o.o.; Kraków; On-site; PLN 356,000 - 489,500; Full time

Benefits offered by this job

Health coverage

Retirement plans

Mobility benefits

Work-life balance

Performance rewards

Job summary

GE HealthCare’s Chief Data and Analytics Office seeks an experienced Engineer to lead ML and GenAI operations, software development, and AI architecture within Enterprise AI. You will build and deploy scalable AI solutions across hybrid cloud, collaborate with data scientists and engineers, and advance model lifecycle management.

The role emphasizes cutting‑edge GenAI tooling, PoCs, and governance, with focus on productionizing models, ensuring security, observability, and cross‑functional

Qualifications

• PhD or Master’s degree in Computer Science, Data Science, Engineering, or a related discipline with a strong focus on engineering and ML/DevOps.
• Advanced hands‑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 of MLOps / GenAIOps tools and frameworks (e.g., MLflow, SageMaker, Bedrock, LangSmith, LangGraph).
• 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 and LangChain architecture.
• Strong understanding of multi‑agent or distributed AI ecosystems, enabling consistent model‑to‑model communication (MCP, A2A) and orchestration.

Responsibilities

• Develop and operationalize ML and GenAI pipelines to enable scalable, reliable, and secure deployment of AI models across GE HealthCare’s enterprise landscape.
• Automate model lifecycle management, including model versioning, CI/CD, testing, deployment, observability, 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—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 (e.g., LangChain, MLflow, Kubeflow, MS Copilot, OpenAI Agent 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.

Skills

Python

AWS

Azure

Kubernetes

MLOps

GenAI

LangChain

Education

PhD or Master’s in Computer Science/Data Science/Engineering

Tools

MLflow

SageMaker

Bedrock

LangSmith

LangGraph

Job description

Job 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. 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.

Core Responsibilities

• Develop and operationalize ML and GenAI pipelines to enable scalable, reliable, and secure deployment of AI models across GE HealthCare’s enterprise landscape.
• Automate model lifecycle management, including model versioning, continuous integration (CI/CD), testing, deployment, observability, 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—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 (e.g., LangChain, MLflow, Kubeflow, MS Copilot, OpenAI Agent 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

• PhD or Master’s degree in Computer Science, Data Science, Engineering, or a related discipline with a strong focus on engineering and ML/DevOps.
• Advanced hands‑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 of MLOps / GenAIOps tools and frameworks (e.g., MLflow, SageMaker, Bedrock, LangSmith, LangGraph).
• 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 and LangChain architecture.
• Strong understanding of multi‑agent or distributed AI ecosystems, enabling consistent model‑to‑model communication (MCP, A2A) and orchestration.

Pay Range

For Poland based positions, Annual Salary Range: 356,000.00 PLN – 489,500.00 PLN. Placement within this range depends on relevant skills and qualifications, prior job‑related experience, and internal equity considerations.

Benefits & Rewards

• Health and 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