Staff Software Engineer

Staff Software Engineer
Hybrid - Boston, MA Remote candidates considered
The role


Reporting to the Director of Engineering, the Staff Software Engineer will own technical strategy and architecture for major product initiatives. This isn't a role where you'll be handed a spec and asked to execute, you'll have significant autonomy and influence over what gets built and how.


You'll lead the design and delivery of complex backend systems that power AI-based healthcare products, while partnering closely with ML and data teams on shared infrastructure.


What you'll do

• Own core backend systems - Design, build, and maintain scalable services, APIs, and platform infrastructure. Ensure reliability, observability, and maintainability.
• Support data pipelines & ML deployment - Partner with data engineers to build pipelines for ingestion, transformation, and analytics. Support ML model deployment and inference infrastructure.
• Lead third-party & clinical integrations - Build and maintain integrations with external vendors, hospital PACS systems (HL7/DICOM-SR), and clinical facilities. Manage DICOM ingestion and validation workflows.
• Influence architecture & best practices - Shape backend architecture, coding standards, testing frameworks, and CI/CD pipelines.
• Foster continuous improvement - Cultivate a team culture of experimentation, iteration, and learning.
• Mentor engineers - Provide technical leadership and guidance on system design, debugging, and engineering practices.

• Bachelor's or Master's in Computer Science, Software Engineering, or equivalent - plus 10+ years of software engineering experience
• Expert-level Python for backend services, automation tools, and data processing systems
• Experience designing scalable distributed systems, microservices, and event-driven architectures
• Proficiency with SQL/NoSQL databases, performance optimization, and data pipelines
• Hands-on AWS experience: Terraform, Docker, Kubernetes, serverless, VPCs, load balancers, and networking fundamentals
• Strong testing, CI/CD, and observability practices
• Knowledge of infrastructure security best practices: secret management, encryption, and access controls
• Excellent communication skills and ability to collaborate across engineering, science, and clinical teams

• Experience with healthcare data standards (DICOM, HL7, DICOM-SR) and hospital PACS integrations
• Exposure to AI/ML-driven platforms or data-intensive systems
• Experience with Metaflow or other modern workflow orchestrators
• Experience with secure network connectivity (VPNs, private endpoints) for clinical environments
• Background in regulated industries (healthcare, fintech, etc.)
• Track record of scaling systems from early-stage to production