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Scarlet is a medical device certification and assessment company that combines clinical, technical, and regulatory expertise with AI agents and software to accelerate certification timelines for AI-enabled medical devices without compromising safety standards. Customers have reduced certification timelines by a year or more and shortened product-update cycles from months to weeks.
As a Software Safety Engineer, you will assess software lifecycle processes and technical documentation for medical device software submitted by customers. You will use AI-assisted workflows to navigate evidence, explore failure modes, develop questions, test hypotheses, and surface inconsistencies for deeper review. Your work will identify software risks and evidence gaps to enable rigorous certification decisions and help safe devices reach patients faster.
Key responsibilities include:
- Assessing software lifecycle processes and technical documentation from customers
- Screening and actioning regulatory insights from latest research, standards, and guidance
- Collaborating with product, engineering, and applied machine learning teams to improve internal systems and tools
- Working with the market access team to expand Scarlet's certification scope to new jurisdictions
- Creating content explaining complex regulatory topics to customers and prospects
- Providing regulatory insights to prospects and customers
You will experiment with workflow improvements as AI model capabilities evolve and contribute to building scalable infrastructure for medical device certification.
REQUIREMENTS:
- Bachelor's degree in computer science or related discipline
- 4+ years' experience in medical device or safety-critical product manufacturing, auditing, or research
- 2+ years' experience developing safety-critical software
- Practical experience with software development fundamentals: software development lifecycle processes, software verification and validation testing, software configuration management, and cybersecurity
- Exceptional written and verbal communication skills
PREFERRED:
- Knowledge or training in medical device software standards (IEC 62304, IEC 81001-5-1)
- Practical experience with generative AI (LLMs, embeddings, RAG, fine-tuning, evaluation/monitoring)
