Sr. Reliability Engineer (Stapling Portfolio / Surgical)

The Sr. Reliability Engineer supports the quality and reliability of advanced stapling technologies throughout the product lifecycle, leading activities ranging from risk assessments and design changes to failure investigations and reliability improvements. This role offers the opportunity to work with software-enabled products, embedded systems, and electronic hardware, making it well suited for engineers with experience in embedded software, circuit board technologies, or complex electromechanical systems.

In partnership with Research & Development, Supplier Quality, Manufacturing, and Complaint Handling teams, you'll help solve complex technical challenges and guide decisions that improve product performance and patient outcomes. This position is based in North Haven, Connecticut, with a minimum of four days per week onsite to support laboratory testing, product investigations, and cross-functional collaboration.

As a Senior Reliability Engineer, you will serve as the quality and reliability lead for products within the CSI Stapling portfolio. You will investigate complex product performance issues, identify failure mechanisms, and apply advanced analytical techniques to drive product improvements and reduce risk. Working closely with Research & Development, Manufacturing, and Supplier Quality teams, you will influence decisions across the product lifecycle through hands-on investigations, data-driven analysis, and design quality expertise.

Primary Responsibilities

• Lead reliability engineering programs including reliability demonstration testing, accelerated life testing, reliability growth initiatives, predictive modeling, and test planning.
• Investigate product performance, field quality, and manufacturing-related issues to identify failure mechanisms, determine root causes, and drive effective corrective actions.
• Apply statistical methods including Design of Experiments (DOE), regression analysis, confidence intervals, hypothesis testing, and trend analysis to support engineering decisions.
• Partner with Research & Development teams to evaluate design changes, improve product robustness, and support verification, validation, and design review activities.
• Conduct hands-on product evaluations, laboratory investigations, and technical assessments to understand product performance and validate engineering hypotheses.
• Lead risk management activities including hazard analysis, Failure Modes and Effects Analysis (FMEA), risk assessments, and maintenance of risk management documentation.
• Review and assess engineering, supplier, and manufacturing changes to ensure quality, reliability, and regulatory requirements are met.
• Analyze complaint, post-market, and quality system data to identify emerging trends and drive product and process improvements.

Required Qualifications

• Bachelor's degree with 4+ years of relevant experience OR Master's degree with 2+ years of relevant experience OR PhD.
• Experience in medical device, pharmaceutical, biotechnology, or other regulated product industries.

Preferred Qualifications

• Experience with design controls, risk management, verification, validation, and engineering change processes.
• Experience supporting embedded software, electronic hardware, circuit board-based, or electromechanical products.
• Experience conducting root cause investigations and resolving product or process quality issues.
• Experience applying statistical methods to product, reliability, quality, or process improvement activities.
• Knowledge of ISO 13485, ISO 14971, IEC 60601, and European Union Medical Device Regulation (EU MDR).
• Experience with reliability methodologies including accelerated life testing, reliability demonstration testing, predictive modeling, and reliability growth analysis.
• Experience using Minitab for Design of Experiments (DOE), regression analysis, confidence intervals, hypothesis testing, and statistical modeling.
• Experience applying structured problem-solving methods including Fault Tree Analysis, Fishbone Analysis, 5 Why investigations, and failure mechanism analysis.
• Experience leveraging artificial intelligence tools to enhance engineering analysis, data evaluation, or technical problem solving.