Software Architect

Description

Position Overview: Responsible for the high-level architecture and design of medical device software, ensuring alignment with system and software requirements. This “hands-on” role requires you to be in our Bedford, NH office to collaborate with project managers and software teams on multiple projects. The role includes reviewing detailed designs, the testing structure, and code, while also focusing on risk management and cybersecurity to ensure device safety for users and clinicians.  It also offers the chance to lead technical initiatives, guide engineering teams, and make a significant impact on the development of medical devices.

Key Responsibilities:

• Architecture  & Design: Develop scalable, secure, and compliant software architecture based on system and software requirements.
• Collaboration  & Leadership: Work closely with project managers and software teams, providing architectural guidance and mentoring engineers.
• Code  Quality & Reviews: Conduct code reviews, enforce coding standards, and ensure high-quality, maintainable code.
• Regulatory Compliance: Ensure adherence to regulatory standards  (e.g., IEC 62304) for medical device software.
• Risk  Management & Cybersecurity: Integrate safety measures and conduct risk assessments to ensure device safety.
• Continuous  Improvement: Advocate for best practices, evaluate new technologies, and enhance development processes.

Requirements

Qualifications:

• Required: Bachelor’s  degree in software engineering, Computer Science, Electrical Engineering,  or a related field; 10+ years of industry experience; proficiency in programming languages (e.g., C, C#, C++, JavaScript); experience with embedded systems, and medical device development; familiarity with Agile/Scrum processes.
• Beneficial: Master’s degree; experience in Class B and C medical devices; Linux OS configuration; familiarity with test-driven development (TDD), CI/CD, and regulatory standards like IEC 62304.
• Preferred:  Experience using generative AI to aid in software development, developing machine learning-based products, knowledge of embedded Linux, real-time operating systems (RTOS), and cybersecurity hardening, as well as familiarity with      Atlassian tools and software development best practices.