Description
Senior Manager, AI/ML EngineeringPosition Summary
We are seeking a Senior Manager, AI/ML Engineering to own the AI/ML engineering portfolio across multiple teams: the roadmap, the platform bets, the AI governance program, and the leadership bench that delivers it. This position plays a key role in supporting the AI Engineering pillar within the Engineering organization, ensuring alignment with organizational goals, operational excellence, and compliance standards.Gifthealth's AI systems talk to patients about their prescriptions every day: agentic voice, chat, and automation running at pharmacy scale on PHI. Where an Engineering Manager owns the delivery and health of their teams, this role owns the function: the roadmap across the AI/ML pillar, the platform bets (which vendors, which models, what gets built in-house), the governance program that keeps a growing agent fleet safe and accountable, and the bench of leaders who deliver it. The Senior Manager translates executive strategy into a portfolio of initiatives, and translates the state of the portfolio back to executives with honest numbers.
Key Responsibilities
- Own the AI/ML engineering roadmap across teams: sequencing, staffing, dependencies, and delivery against committed outcomes
- Manage engineering managers and lead engineers; build the leadership bench through hiring, coaching, and succession planning
- Own major platform decisions: build-versus-buy, vendor selection and migration, and model strategy across foundation-model providers, with cost and risk quantified
- Own the AI governance program: documentation standards across the agent fleet, evaluation and release gates, responsible AI review, and the compliance posture of AI systems that handle PHI
- Define and report the key performance indicators for production AI: containment, deflection, quality, latency, cost per interaction, and the trendlines behind each
- Own reliability at the portfolio level: production support standards, incident escalation, and the postmortem discipline across all AI/ML teams
- Partner with executives, product, operations, data, and compliance to set strategy and commitments; represent AI Engineering in cross-functional and client-facing forums
- Drive 0-to-1 initiatives from evaluation through proof of concept to general availability, and kill the ones that should not ship
- Education: Bachelor's degree in Computer Science or a related field, or equivalent experience
- Licensure/Certification: Not applicable
- Experience: 12+ years of software engineering experience, including substantial production ML or LLM-based systems experience; 5+ years leading engineering teams, including experience managing managers or leads.
- Skills:
- A track record of owning an AI/ML portfolio or function: roadmap, headcount, vendor relationships, and delivery across multiple concurrent initiatives
- Demonstrated 0-to-1 delivery of AI-enabled products, from proof of concept to general availability, including the quality and governance work that requires
- Experience establishing AI governance, evaluation, or responsible AI practices at an organizational level
- Fluency in the modern LLM stack (retrieval-augmented generation, prompt and context engineering, evaluation frameworks, fine-tuning or adaptation) and in cloud AI platforms (AWS Bedrock or equivalent)
- Executive-level communication: able to set strategy with leadership and defend tradeoffs with data
- Conversational AI at scale: voice or chat systems with measurable containment or deflection improvements, including platform migrations
- Healthcare, pharmacy, or regulated-industry background; working knowledge of HIPAA, HITRUST, or equivalent regimes applied to AI systems
- Experience scaling an AI/ML organization through rapid growth while maintaining quality and retention
- Experience with contact-center AI and the operational realities of systems that front live patient or customer conversations
- Familiarity with Ruby on Rails and PostgreSQL environments that AI systems integrate with
- Location: Remote (Columbus, OH office)
- Schedule: Full-time; occasional evening and weekend hours
- May require availability during evenings and weekends or flexibility for escalations; includes regular virtual meetings with internal and external stakeholders.
- Regular meetings with executives, product, operations, data, and compliance teams to set strategy and commitments.
- Not applicable — this is a remote, desk-based role with standard computer and virtual-meeting work requirements.
Status: Full-time FLSA: Exempt
Equal Employment Opportunity (EEO) StatementGifthealth 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.
DisclaimerThis 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.
Skills Required
- Bachelor's degree in Computer Science or a related field, or equivalent experience
- 12+ years of software engineering experience
- Substantial production machine learning or LLM-based systems experience
- 5+ years leading engineering teams, including managing managers or leads
- Experience owning an AI/ML portfolio or function, including roadmap, headcount, vendor relationships, and delivery
- Demonstrated 0-to-1 delivery of AI-enabled products from proof of concept to general availability
- Experience establishing AI governance, evaluation, or responsible AI practices at an organizational level
- Fluency in retrieval-augmented generation, prompt and context engineering, evaluation frameworks, and fine-tuning or model adaptation
- Experience with cloud AI platforms such as AWS Bedrock or equivalent
- Executive-level communication and ability to defend strategic tradeoffs with data
- Experience with conversational AI at scale, including voice or chat systems and platform migrations
- Healthcare, pharmacy, or regulated-industry experience, including knowledge of HIPAA, HITRUST, or equivalent regimes
- Experience scaling an AI/ML organization while maintaining quality and retention
- Experience with contact-center AI and systems supporting live patient or customer conversations
- Familiarity with Ruby on Rails and PostgreSQL environments
What We Do
Gifthealth is a digital pharmacy and access platform that streamlines prescription fulfillment, reduces patient out-of-pocket costs, and improves persistence for biopharma brands and their clinics. As the first digital pharmacy to offer direct-to-patient services at scale, it connects prescribers, patients, and partners through a seamless, end-to-end experience to remove barriers across the entire prescription journey.






