[Remote] Lead AI Engineer

Note: The job is a remote job and is open to candidates in USA. Gifthealth is revolutionizing healthcare by simplifying prescription management and health services. The Lead AI Engineer will build and scale the AI engineering function, leading a team to implement advanced AI systems while collaborating with cross-functional teams.

Responsibilities

• Designs and builds agentic AI systems including LLM orchestration, RAG pipelines, and multi-agent frameworks
• Leads, mentors, and grows AI Engineers, conducting one-on-one meetings, performance reviews, and identifying career development opportunities
• Works with the Talent Acquisition team to recruit and hire AI Engineers through defining role requirements, screening candidates, and leading technical interviews
• Establishes engineering practices, coding standards, and technical processes for AI systems
• Partners with ML Engineers, Prompt Engineers, and Product on cross-functional AI initiatives
• Drives build/buy/integrate decisions; evaluate AI tooling and vendor solutions

Skills

• Bachelor's degree in computer science, AI/ML, or a related field OR 2–4 years of equivalent practical experience
• 6+ years of software engineering experience with 3+ years in AI/ML systems; 2+ years of management or tech lead experience; history of building and shipping production AI systems
• Knowledge of LLM architectures and orchestration patterns; RAG systems and vector databases; production AI/ML system design; software engineering best practices; and leadership and management principles
• Python and AI/ML development skills
• LLM API integration skills
• System architecture and design skills
• Technical hiring and interviewing skills
• Team leadership and mentorship skills
• Ability to balance hands-on building with team leadership
• Ability to hire and develop engineering talent
• Ability to drive technical decisions across teams
• Ability to communicate with technical and non-technical stakeholders
• Master's degree in computer science or AI/ML
• Experience in healthcare or regulated industries; history of building teams from scratch; FDA or clinical trial software experience
• Knowledge of the healthcare domain and HIPAA compliance; FDA software validation; human-in-the-loop ML systems; graph databases and knowledge graphs
• GPU-accelerated processing skills
• Distributed systems skills
• Cloud platform (AWS, GCP) skills
• ML Ops tooling skills
• Ability to navigate ambiguity in early-stage product development
• Ability to establish engineering culture and practices from scratch
• Ability to influence without authority across functions

Company Overview