Senior Manager of AI/ML Engineering

Gifthealth Inc•Columbus, OH

just now•$176,000 - $215,000•Remote

About The Position

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.

Requirements

Bachelor's degree in Computer Science or a related field, or equivalent 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
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

Nice To Haves

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

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