Head of Applied AI Engineering
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Job Description
Head of Applied AI Engineering leading AI applications in healthcare and wellness. Responsible for high-impact technical execution and delivery across diverse client bases.
Responsibilities:
- Build, hire, and mentor a high-performing organization of Applied AI Engineers.
- Own the department charter, ROI performance, and technical best practices.
- Own and manage the technical success of agentic AI deployments, ensuring systems are HIPAA-compliant, scalable, and deeply integrated with client EHR/EMR, CRM, and claims data systems.
- Act as the primary technical executive for strategic enterprise accounts, translating complex business workflows into production-ready AI configurations.
- Partner with Sales and Growth teams to lead technical discovery, underwrite high-ROI use cases, and drive expansion/upsell opportunities within existing accounts.
- Collaborate with Platform Engineering and Product teams to turn field-derived configuration patterns into reusable components and platform improvements.
- Oversee the design of robust data ingestion pipelines, real-time agent infrastructure, and output guardrails to ensure agents remain compliant and safe.
Requirements:
- 10+ years in hands-on engineering & delivery leadership in high-stakes environments; proven end-to-end ownership of outcomes.
- Strong backend + data foundation — APIs, real-time services, and scalable data pipelines (ETL/ELT, streaming).
- Technical degree in Computer Science, Software Engineering or similar
- Real-time & distributed systems — event-driven architectures, WebSockets/streaming, high-throughput production systems.
- Client-facing + team leadership — leads enterprise engagements and high-talent FDE teams; translates workflows into scalable, ROI-driven systems; thrives in 0→1 and scale environments.
- Business development skills to act as a key player way in ‘land and expand’ motions across enterprise accounts
- Significant startup experience throughout career, playing a key role as a founding member or having an impact at an early stage startup (less than 150 employees).
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