Job Description Summary

The Early Career AI Automation Engineer will contribute to the development and application of AI assisted test automation and analysis solutions for patient monitoring systems. Under guidance from senior engineers, this role focuses on accelerating verification cycles, improving automation efficiency, and supporting predictable, timeboxed releases while learning to operate within a regulated medical device quality environment.

GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Job Description

Roles and Responsibilities

• Contribute to building and enhancing AI‑assisted test selection and impact analysis mechanisms to help reduce verification cycle time.

• Designing RAG models, agent workflows, and multi-step reasoning models.

• Build agentic automation solutions to streamline verification and validation process.

• Unstructured data analysis, Integrating ML/GenAI models and LLM orchestration into end-user AI applications.

• Conduct research and stay updated with the latest advancements in AI technologies.

• Translate AI research into business solutions.

• Assist in generating intelligent execution summaries from automated test runs to support faster engineering and quality reviews.

• Support efforts to increase effective automation coverage by applying AI‑based recommendations under human‑in‑the‑loop review and approval.

• Balance automation efficiency with risk awareness, traceability, and in compliance to QMS.

• Participate in CI pipelines and HALT environments to support continuous validation and early defect discovery across system builds.

• Apply AI and data‑driven techniques to log analysis, Reliability test reporting, and failure analysis, helping reduce time needed for go/no‑go release decisions.

• AI based root cause analysis (RCA) by correlating failures across logs, test results, and system configurations under mentorship from senior engineers.

Required Qualifications

• Master’s degree (MS) in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related field.

• 2+ years of project experience in Python, Java, or similar, with exposure to automation frameworks, ML libraries, or data analysis tools.

• Proficiency in deep learning frameworks.

• Academic projects or internships involving AI for quality, and data analysis.

• Passion for medical AI, responsible, good teamwork and communication skills.

• Understanding of software testing concepts, CI/CD fundamentals, and AI/ML techniques (classification, anomaly detection, NLP, or similar).

• Hands on experience with LLM & Prompt engineering

Desired Qualification

Additional Information