Principal AI Product Engineer (AI)

TL;DR

Principal AI Product Engineer (AI): Designing and implementing scalable AI capabilities, agents, and conversational interfaces across a healthcare product portfolio with an accent on RAG, vector search, and model orchestration. Focus on building enterprise-ready AI infrastructure on Databricks and creating shared services to accelerate AI deployment.

Location: Remote (Must be based in the USA)

Company

hirify.global is a healthcare technology corporation focused on transforming the healthcare industry through innovative software solutions.

What you will do

• Design and implement scalable AI capabilities, including agents and conversational interfaces, as reusable components across multiple products.
• Establish integration patterns for conversational AI, RAG, vector search, and model orchestration.
• Leverage the Databricks platform (Unity Catalog, Delta, Workflows, Model Serving) to build enterprise-ready AI foundations.
• Standardize infrastructure and create shared services/SDKs to reduce time-to-production for AI features.
• Define governance, monitoring, and evaluation frameworks to ensure AI systems are reliable, secure, and production-ready.
• Collaborate with product, engineering, and data platform teams to translate AI capabilities into scalable product solutions.

Requirements

• 8+ years of engineering experience, including expertise in distributed systems.
• Deep experience with Databricks platform architecture and hands-on implementation of Genie.
• Proven experience designing RAG pipelines and model-serving architectures.
• Strong backend engineering expertise in Python, including APIs and microservices.
• Experience designing shared services or internal platforms.
• Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related technical field.

Nice to have

• Advanced degree (MS or PhD) in AI, Machine Learning, or Data Science.
• Full-stack development experience with React, Next.js, and TypeScript for AI-driven interfaces.
• Strong understanding of cloud-native architectures (AWS, Azure, or GCP).
• Knowledge of data engineering and pipeline patterns (ETL/ELT).
• Experience with AI governance, model evaluation, and observability frameworks.

Culture & Benefits

• Comprehensive health, dental, vision, life, and disability insurance.
• 401k retirement program and employee incentive plans.
• Paid time off and tuition reimbursement for professional development.
• Collaborative work environment that encourages critical thinking and autonomy.
• Access to on-site and online exercise classes.