Principal AI Engineer (AI)

Location: Atlanta, Georgia, United States of America; other location: Northridge, California, United States of America. Workplace type: Flexible.

Salary: $138,000–$234,000 for U.S. locations; $153,000–$261,000 for California, Seattle, Washington DC, Boston, and New York City locations.

Company

hirify.global is a full-stack insulin delivery company developing intelligent dosing systems and predictive diabetes-care solutions.

What you will do

• Prototype AI/ML models, LLM-powered agents, and tools against real business data and workflows.
• Build, evaluate, deploy, and drive adoption of production capabilities on the MIA stack, including Databricks, LangGraph/LangSmith, and enterprise agent platforms.
• Integrate agents and models with APIs, SSO/SAML/OAuth, Salesforce, SAP, and enterprise data pipelines.
• Establish reusable patterns for agent design, tool-calling, retrieval, and evaluation; review and quality-gate other engineers’ designs.
• Feed deployment learnings into the MIA platform, shared tooling, and reusable-pattern roadmap while partnering with the Product Manager, AI & Data Science.
• Build for a regulated medical-device environment with safety, privacy, compliance, auditability, and human-in-the-loop controls.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related technical field with 8+ years of relevant experience, or an advanced degree with 6+ years of relevant experience.

Nice to have

• Production delivery of LLM-powered systems or ML models beyond prototypes, evaluations, or internal demos.
• Strong system design and end-to-end ownership from prototype through production deployment.
• Technical leadership or direction of other engineers, including work review.
• Stakeholder-facing communication and the ability to scope ambiguous problems and explain latency, cost, and model-risk trade-offs to non-technical leaders.
• Hands-on experience with Databricks, LangGraph, LangSmith, vector databases, and managed RAG/retrieval.
• Forward-deployed or embedded engineering experience using real business data, workflows, and constraints.
• Experience integrating AI or software systems with complex enterprise environments, including APIs, identity/authentication, systems of record, and data pipelines.
• Experience with formal MLOps disciplines and handoff to model operations.
• Experience in regulated industries such as medical devices, healthcare, or financial services; familiarity with HIPAA, audit, and validation requirements.

Culture & Benefits

• Full-time employment with a flexible workplace type.
• Competitive compensation and a short-term incentive plan.
• Health, dental, vision, life insurance, disability coverage, HSA/FSA, and dependent daycare spending account for eligible regular employees.
• Paid time off and holidays, 401(k) with company match, Employee Stock Purchase Plan, and Employee Assistance Program.
• Equal employment opportunity and reasonable accommodations are provided for qualified individuals with disabilities.