Software Engineer III

Cleerly is a healthcare company developing AI-driven precision diagnostic solutions for heart disease. The Software Engineer III will drive technical initiatives across computational imaging pipelines, deploying and scaling regulated AI systems while influencing architecture, ensuring medical-quality standards, mentoring engineers, and supporting system reliability.

Responsibilities:

• Build and deploy scalable AI services and computational imaging pipelines to production, ensuring robust, high-availability infrastructure for our machine learning algorithms
• Contribute to the system architecture's design and make pragmatic trade-offs that balance performance, security, and maintainability
• Own full lifecycle delivery of complex features, from architectural planning and API design to implementation and post-release observability
• Support the high availability and observability of our services; improve alerting, logging, and incident response across the stack
• Uphold strong engineering standards via code reviews, technical mentorship, and design documentation
• Collaborate closely across AI and engineering to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation
• Implement robust testing mechanism and validation strategies to ensure compliance with our Quality Management System and regulatory standards

Requirements:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent experience)
• 5–8 years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar)
• Demonstrable capability in designing, implementing, and securing RESTful web services
• Experience in MLOps orchestration and cloud deployment (Docker, Kubernetes)
• Experience with AWS, GitHub, and continuous integration pipelines
• Proven track record of delivering scalable systems in production environments
• Strong systems thinking with the ability to evaluate tradeoffs in scalability, reliability, and maintainability
• Experience designing for observability and operational excellence (e.g., logs, alerts, dashboards, runbooks)
• Comfortable operating in ambiguity and driving clarity across product, engineering, and business stakeholders
• Experience designing and optimizing end-to-end medical imaging pipelines in a production environment and familiarity with HIPAA/HITRUST security requirements
• Hands-on experience with Computer Vision and Deep Learning techniques used for medical image processing