Engineering Manager

We're hiring an Engineering Manager to lead and grow the team building Cadence's Clinical Intelligence platform, the AI system that helps clinicians deliver safe, evidence-based medication recommendations at scale. This role sits at the intersection of clinical, product, AI, and design partners, translating patient data, clinical protocols, and deterministic safety rules into production systems clinicians trust. You'll take these capabilities from concept to production, meeting reliability and quality standards that approach those of medical devices.

• →Define and drive the technical vision and architecture for Cadence's Clinical Intelligence platform, balancing AI innovation with clinical safety, reliability, and explainability.
• →Partner with clinical, product, design, and AI teams to shape the roadmap for clinician-supervised decision support and medication recommendation systems.
• →Lead development of AI-powered clinical workflows that combine patient data, evidence-based protocols, deterministic safety rules, and clinician oversight into trusted decision systems.
• →Hire, mentor, and grow a team of AI, backend, and full-stack engineers delivering safe, scalable clinical intelligence.
• →Own the design, development, and operation of the services, infrastructure, and evaluation frameworks powering medication recommendation and clinical decision support engines.
• →Establish engineering standards, testing strategies, observability, and validation processes that ensure clinical correctness, system reliability, and regulatory readiness.
• →Drive a culture of quality, ownership, and continuous improvement across the engineering team.

• 5+ years of experience in software engineering, including 2+ years in a people management role.
• Experience leading development of complex software products from 0 to 1, preferably within healthcare, enterprise SaaS, or another regulated industry.
• Experience presenting technical strategy to executive stakeholders and engaging directly in architecture and code reviews.
• Experience building backend systems using modern cloud infrastructure (AWS or GCP), relational databases (Postgres or MySQL), and messaging systems such as SQS or Kafka.
• Experience with Go.
• Fluency with LLM APIs, prompt engineering, and AI-assisted development tools; demonstrated experience building or evaluating AI-powered systems in production.