Staff Software Engineer

What you'll work on

• Set the automation and quality strategy. Define the vision, reference architecture, and roadmap for scalable automation and continuous verification across product lines, and drive adoption as a recognized technical authority.
• Architect lifecycle automation. Design and build reusable frameworks, services, simulators, and engineering tools that enable requirements-based and risk-based verification at the unit, component, integration, system, regression, and release levels.
• Integrate quality into delivery. Embed automated quality controls, traceability, diagnostics, and actionable quality signals into CI/CD pipelines so teams receive rapid, reliable feedback throughout the development life cycle.
• Engineer connected-system integration. Develop robust integration capabilities across embedded devices, clinician applications, interfaces, services, data flows, and representative hardware or simulated environments.
• Apply AI responsibly. Incorporate Abbott's Responsible, Safe, Transparent, Fair, and Impactful AI principles into daily automation and quality engineering. Follow established governance and intended-use boundaries; protect sensitive data; verify generated outputs; preserve source traceability; document limitations; and maintain meaningful human oversight and accountability.
• Advance AI-enabled engineering. Use AI copilots, large language models, and agentic workflows to improve coverage analysis, automation development and maintenance, failure investigation, and engineering productivity where their use is appropriate, validated, reproducible, and auditable.
• Lead technical quality. Partner with software, systems, quality, cybersecurity, and product teams to improve architecture, prevent defects, close coverage gaps, strengthen design reviews, and make quality measurable across programs.
• Ensure safety, compliance, and continuous improvement. Keep automation and AI-assisted engineering aligned with applicable medical device standards, including IEC 62304, ISO 14971, ISO 13485, and 21 CFR 820. Evaluate emerging tools, measure their impact on product quality and delivery, scale proven approaches, and mentor engineers in their effective and responsible use.

Required Qualifications

• Bachelor's degree in computer science, Software Engineering, or a related technical field; an advanced degree is a plus.
• 10+ years of software engineering experience with a strong focus on automation, software quality, system integration, verification, or platform and tools engineering, including technical leadership of complex initiatives.
• Deep hands-on experience designing test automation architecture, reusable frameworks, and CI/CD-integrated quality capabilities for complex software systems.
• Demonstrated ability to integrate quality across requirements, design, implementation, integration, release, and maintenance using risk-based coverage, traceability, and measurable evidence.
• Strong software engineering fundamentals and proficiency in Python, with the ability to design maintainable production-grade tools, services, and automation.
• Hands-on experience using AI copilots, large language models, or agentic workflows in daily engineering work, with disciplined validation of accuracy, security, privacy, traceability, limitations, and appropriate human oversight.
• A track record of setting technical direction, mentoring engineers, leading design reviews, and influencing decisions across teams and product lines.

Preferred Qualifications

• Experience in regulated, safety-critical, or high-reliability software domains such as medical devices, aerospace, automotive, or similar industries.
• Experience with connected products, embedded systems, mobile or desktop applications, cloud services, hardware-in-the-loop environments, or device simulators.
• Familiarity with evaluating AI-assisted engineering workflows, including output quality, hallucination and bias risks, reproducibility, explainability, and ongoing performance monitoring.
• Strong systems thinking with an emphasis on reliability, observability, traceability, explainability, human oversight, and the ability to influence without authority.