Principal AI Product Engineer
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Job Description
Designing scalable AI capabilities and components for healthcare improvement. Collaborating with product teams, and implementing advanced technologies using the Databricks platform.
Responsibilities:
- Design and implement scalable AI capabilities across our product portfolio
- Turn advanced models, agents, and conversational interfaces into reusable components that can be embedded across multiple software solutions
- Work closely with product, engineering, and data platform teams
- Establish integration patterns for technologies such as conversational AI, RAG, vector search, and model orchestration while leveraging the Databricks platform
- Accelerate the delivery of AI-powered features by standardizing infrastructure, creating shared services, and defining governance, monitoring, and evaluation frameworks that ensure AI systems are reliable, secure, and production-ready
Requirements:
- 10 or more years of experience in applicable fields
- Advanced AI/ML engineering skills, including large language models (LLMs), RAG architectures, agent frameworks, and conversational AI systems
- Expertise in the Databricks ecosystem (Unity Catalog, Delta Lake, Workflows, Model Serving, Genie)
- Strong backend engineering in Python, including APIs, microservices, and distributed systems design
- Experience building and deploying production AI systems, model serving pipelines, and scalable inference architectures
- Proficiency with vector databases, embeddings, semantic search, and retrieval frameworks
- Full-stack development experience including React, Next.js, TypeScript, and modern frontend frameworks for building AI-driven user interfaces
- Experience designing API-first architectures, REST/GraphQL services, and AI-enabled application layers
- Experience building shared platforms, SDKs, and internal developer tooling
- Strong understanding of cloud-native architectures (AWS, Azure, or GCP)
- Knowledge of data engineering and pipeline patterns, including ETL/ELT workflows and large-scale data processing
- Experience with AI governance, model evaluation, monitoring, and observability frameworks
- Strong understanding of performance, cost, and latency optimization for AI-powered applications
- Ability to collaborate across product, data, engineering, and executive leadership to translate AI capabilities into scalable product solutions.
- Hands-on experience implementing Genie
- Deep experience with Databricks platform architecture
- Strong backend engineering expertise (Python required)
- Experience designing RAG pipelines and model-serving architectures
Benefits:
- Health, dental, vision, life and disability insurance
- 401k retirement program
- Paid time off
- Participation in Premier’s employee incentive plans
- Tuition reimbursement and professional development opportunities
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