Director, Engineering (Interventions)
New
C
Clover HealthHealth Tech
Remote - USAFull-TimeDirector
Salary$223,100 — $275,000 USD
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Job Details
- Experience
- 12+ years of engineering (IC + leadership)
- Required Skills
- Artificial IntelligenceMachine LearningCI/CDLLM
Requirements
- 12+ years of engineering (IC + leadership), with a focus on healthcare data, clinical interoperability, or ML-driven healthcare products.
- Deep familiarity with clinical data structures (e.g., ICD-10) and best practices for building high-integrity clinical data pipelines.
- Proven experience leading cross-functional teams of engineers, data scientists, and clinical operators to deliver complex software in regulated environments.
- Experience managing ML model lifecycles and deploying LLM-driven features to improve product accuracy and engagement.
- Experience implementing and scaling AI-assisted development workflows (e.g., AI code assistants, automated testing, or AI-driven CI/CD).
- Proven track record of mentoring and developing engineering managers and senior individual contributors.
- Demonstrated ability to cultivate a high-performance engineering culture focused on velocity, quality, and psychological safety.
- Experience leading organizational change, including structural re-orgs and process evolution.
- Strong proficiency in strategic resource allocation, capacity planning, and managing technical debt.
Responsibilities
- Own the Interventions technical roadmap, driving the strategy for improved clinical data accuracy and the effective closure of clinical care gaps.
- Lead the diagnostic precision strategy by optimizing assessment surfacing, implementing member-specific modeling, and advancing the extraction of high-quality evidence from clinical data sources.
- Oversee the scaling of Interventions systems to accommodate a rapidly growing member base, including the core data infrastructure overhaul and ensuring ML pipeline stability.
- Manage cross-functional partnerships with Clinical Operations, Product, and cross-functional teams’ leadership to ensure technical investments remove clinical bottlenecks.
- Drive the adoption of an AI-powered Software Development Life Cycle (SDLC), leveraging AI tools to accelerate coding, testing, and deployment processes.
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