AI Engineering Director

1w1 week ago

Abacus Insights

US · Full-time · $280,000 – $380,000

About this role

Abacus Insights is transforming how data works for health plans. Our mission is to make healthcare data usable, so people responsible for care and cost decisions can act faster, with confidence. We break down data silos to create a single, trusted data foundation that powers better decisions.

As AI Engineering Director, you will set technical direction for AI/ML solutions that solve high-impact customer and internal problems, from discovery through production. You’ll partner closely with Engineering, Product, and customer-facing teams to translate complex business needs into scalable, secure, and reliable AI capabilities. You’ll lead by example, driving design and engineering excellence.

Your day-to-day involves leading architecture, design, and implementation of AI/ML systems from concept to production. You’ll define technical standards, best practices, and AI engineering patterns across teams while guiding model development, evaluation, deployment, and lifecycle management. Partner with Product and Engineering leaders on AI strategy and roadmap.

We are bold, curious, and collaborative because the best ideas come from working together. Backed by $100M from top investors, our platform enables GenAI use cases with clean, connected, reliable healthcare data. Join us to mentor engineers, ensure responsible AI practices, and drive innovation initiatives.

Requirements

8-10 years of experience in data engineering and architecture roles, with 2+ years in an engineering leadership role
Strong experience leading ML/AI engineering efforts from concept through production in fast-moving organizations
Exposure to Databricks, Mosaic AI Gateway, and related Data + AI technologies
Working knowledge of RAG architectures, SQL Agents, and MCP
Strong analytical and problem-solving skills, with the ability to translate complex problems into clear execution plans
Proven ability to mentor and coach less-experienced engineers, providing technical guidance, feedback, and growth support across complex AI initiatives
Acts as a technical mentor across teams, elevating engineering quality by developing junior engineers and modeling best practices in AI system design and delivery

Responsibilities

Lead architecture, design, and implementation of AI/ML systems from concept to production
Define technical standards, best practices, and AI engineering patterns across teams
Translate complex business problems into scalable AI solutions
Guide model development, evaluation, deployment, and lifecycle management
Partner with Product and Engineering leaders on AI strategy and roadmap
Mentor senior and junior engineers and raise overall technical maturity
Ensure responsible AI practices, security, privacy, and compliance
Evaluate emerging technologies and drive innovation initiatives