Lead AI Engineer at giftHEALTH

Columbus, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Aug, 26

Salary

190000.0

Posted On

28 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

LLM Orchestration, RAG Pipelines, Agentic AI Systems, Python, System Architecture, Team Leadership, Technical Hiring, AI/ML System Design, Vector Databases, Multi-agent Frameworks, ML Ops, Cloud Platforms, HIPAA Compliance, GPU-accelerated Processing, Distributed Systems, Knowledge Graphs

Industry

technology;Information and Internet

Description

Description About Us At Gifthealth, we're revolutionizing the way people experience healthcare by simplifying the process of managing prescriptions and health services. Our mission is to provide a seamless, personalized, and efficient healthcare experience for all our customers. We're a dynamic, innovative, and customer-centric company dedicated to making a positive impact on people's lives. Position Summary Reporting to the Director of AI Engineering, the Lead AI Engineer is responsible for building, managing, and scaling Gifthealth's AI engineering function. This position combines hands-on technical work with team leadership: architecting and implementing agentic AI systems while building, developing, and leading a team of AI Engineers. The Lead AI Engineer drives technical decisions across LLM orchestration, RAG pipelines, and production AI infrastructure, while establishing engineering practices, R&D functions, and growing team capabilities. We are seeking a Lead AI Engineer to partner ML Engineers, Prompt Engineers, and Product teams, ensuring alignment with organizational goals, operational excellence, and compliance standards. Key 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 Qualifications Education: Bachelor’s degree in computer science, AI/ML, or a related field OR 2–4 years of equivalent practical experience (Required) Master’s degree in computer science or AI/ML (Preferred) Licensure/Certification: None 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 (Required) Experience in healthcare or regulated industries; history of building teams from scratch; FDA or clinical trial software experience (Preferred) Knowledge, Skills, & Abilities: 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 (Required) Knowledge of the healthcare domain and HIPAA compliance; FDA software validation; human-in-the-loop ML systems; graph databases and knowledge graphs (Preferred) Python and AI/ML development skills (Required) LLM API integration skills (Required) System architecture and design skills (Required) Technical hiring and interviewing skills (Required) Team leadership and mentorship skills (Required) GPU-accelerated processing skills (Preferred) Distributed systems skills (Preferred) Cloud platform (AWS, GCP) skills (Preferred) ML Ops tooling skills (Preferred) Ability to balance hands-on building with team leadership (Required) Ability to hire and develop engineering talent (Required) Ability to drive technical decisions across teams (Required) Ability to communicate with technical and non-technical stakeholders (Required) Ability to navigate ambiguity in early-stage product development (Preferred) Ability to establish engineering culture and practices from scratch (Preferred) Ability to influence without authority across functions (Preferred) Work Environment Location: Remote Schedule: 8:00 A.M. to 5:00 P.M. Monday through Friday with night and weekend hours on occasion as determined by the needs of the business. Regular meetings with internal AI Engineering, Prompt Engineering, ML Engineering, Software Engineering, ML Ops Engineering, Data Science, HR, and product management teams. This role may also have meetings with AI/LLM, cloud, and ML Ops vendor and technology partner representatives. Key Essential Functions Must be able to remain in a stationary position for extended periods while writing or reviewing documentation Must be able to work on a computer for the entire shift Must be able to attend virtual meetings with cross-functional teams Employment Classification Status: Full-time FLSA: Exempt Equal Employment Opportunity (EEO) Statement Gifthealth is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind. All employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, transgender status, national origin, age, disability, veteran status, or any other legally protected status. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you do not meet every requirement but still feel you would be a great fit for this role, we encourage you to apply! Disclaimer This job description is intended to describe the general nature and level of work being performed. It is not intended to be an exhaustive list of all responsibilities, duties, or skills required of personnel. Gifthealth reserves the right to modify job duties or descriptions at any time.

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Responsibilities

The Lead AI Engineer is responsible for architecting and scaling agentic AI systems, including LLM orchestration and RAG pipelines. The role combines hands-on technical implementation with the leadership, mentoring, and recruitment of a team of AI engineers.