Head of AI Engineering & Enablement
New
United States, Pacific Time Zone preferredFull-TimeManager
Salary$224,000–$256,000 USD annually
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Job Details
- Experience
- 8+ years
- Required Skills
- Software EngineeringHIPAA
Requirements
- 8+ years of experience in software engineering, applied AI, technical product roles, or related technology disciplines.
- Strong hands-on engineering background with the ability to design, build, and ship production systems.
- Deep experience developing and deploying AI solutions, including multi-agent systems, RAG architectures, LLM workflows, and AI-powered automation.
- Experience building integrations with enterprise systems, APIs, knowledge platforms, and data sources.
- Strong understanding of agent frameworks, MCP servers, retrieval strategies, and AI orchestration patterns.
- Experience working in healthcare, HIPAA-regulated environments, or similarly regulated industries with strict data privacy requirements.
- Proven ability to identify operational inefficiencies and translate business workflows into scalable technology solutions.
- Strong process re-engineering mindset with the ability to improve systems before automating them.
- Demonstrated experience driving AI adoption and behavioral change across non-technical teams.
- Experience leading and developing small engineering teams while maintaining hands-on involvement.
- Excellent communication skills with the ability to collaborate with executives, business leaders, and technical teams.
Responsibilities
- Partner with executive leadership and functional stakeholders to identify, prioritize, and execute AI opportunities that create measurable operational impact.
- Develop and maintain an AI opportunity roadmap based on business value, feasibility, return on investment, and strategic priorities.
- Re-engineer existing workflows and operating processes before applying automation to ensure AI solutions improve how work is performed.
- Design, build, deploy, and maintain high-value internal AI agents, automations, and intelligent workflows.
- Develop multi-agent systems, retrieval-augmented generation (RAG) pipelines, agent orchestration frameworks, and secure integrations with enterprise systems.
- Own AI architecture patterns, including context layers, knowledge connectors, permission-aware retrieval, API integrations, and reusable AI frameworks.
- Establish governance standards for AI usage, including security controls, data-handling practices, risk management frameworks, and compliance requirements.
- Ensure AI solutions meet healthcare privacy and security expectations, including protection of sensitive information and regulated data.
- Create enablement programs that help teams adopt AI effectively through training, templates, office hours, and practical resources.
- Lead and mentor a small engineering team while remaining deeply involved in hands-on technical delivery.
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