Senior Software Engineer, Security Infrastructure

Cadence is a clinical AI company that delivers continuous, proactive care for older adults with chronic conditions. The Senior Software Engineer, Security Infrastructure will build scalable security infrastructure that embeds compliance and risk controls directly into the Cadence platform.

Responsibilities:

• Embed directly within Product and Platform Engineering teams to implement security-critical features and components of Cadence's platform, and drive teams toward secure architectural and implementation decisions as needed
• Build security capabilities that differentiate Cadence and influence the broader healthcare ecosystem, including reusable security primitives, contributions to open standards and open-source initiatives, and partnerships with customers and vendors to raise the bar for privacy, interoperability, and secure AI adoption
• Design and implement security controls across cloud infrastructure, Kubernetes, CI/CD systems, endpoints, identity systems, secrets management, and broader platform security primitives to keep core systems secure
• Build AI governance processes, frameworks, and safeguards that help ensure Cadence's AI systems are safe, reliable, fair, and aligned with patient safety outcomes

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent work experience
• 3+ years of software engineering experience, with at least 2+ years building and shipping real systems or infrastructure
• Strong ability to navigate and reason across the stack - quickly understanding unfamiliar codebases, architectures, and tooling ecosystems
• Ability to identify patterns and design scalable 'golden paths' (e.g., logging, access controls, network security) that work across teams
• Effective communicator who translates technical findings into clear designs, builds alignment, and drives initiatives from concept to execution
• Demonstrated interest in security and the ability to think adversarially - approaching system design with rigor, considering failure modes, and leveraging modern tools to accelerate solutions