Principal AI/ML Engineer (Data Analytics & AI)

Location: Indianapolis, Indiana; Remote in Indiana; Huntsville, Alabama; or Pleasant Prairie, Wisconsin, United States. Applicants must be authorized to work full-time in the United States. Travel: 0–10%.

Anticipated wage: $69,000–$165,000 annually, plus potential company bonus.

Company

hirify.global develops life-changing medicines and uses data, AI, and digital solutions to improve drug commercialization, patient access, affordability, and outcomes.

What you will do

• Build agentic AI platforms, agent-to-agent orchestration frameworks, multi-agent workflows, tool and API integration layers, and secure connections to enterprise and partner systems.
• Design scalable data pipelines and analytics-ready platforms integrating enterprise, vendor, and third-party partner data.
• Productionize predictive models, LLM solutions, RAG systems, and agentic workflows for reporting, decision support, market access, customer outreach, resource allocation, and revenue protection.
• Engineer end-to-end ML pipelines covering feature engineering, training, fine-tuning, inference, feedback, versioning, registries, experiment tracking, evaluation, deployment, and rollback.
• Implement model serving, containerization, inference optimization, observability, tracing, cost and latency monitoring, drift detection, and AI evaluation in production.
• Apply governance, privacy, regulatory compliance, de-identification, PHI/PII protection, data residency, and auditability while partnering with data scientists, product managers, business users, and technical stakeholders.

Requirements

• Master’s degree in Computer Science, Computer Engineering, Data Science, or a related quantitative or technical field plus at least 1 year of professional experience implementing technical systems; or Bachelor’s degree in one of these fields plus at least 3 years of such experience.
• Authorization to work full-time in the United States is required.
• Lilly will not provide work authorization or visa sponsorship, including for F-1 CPT/OPT/STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.
• Foundational knowledge of communication, leadership, teamwork, problem solving, business acumen, solution and blueprint definition, architecture, governance, technical standards, project delivery, and the industry.
• Ability to engage business stakeholders, elicit and translate requirements, define solutions, ensure traceability, and communicate with technical and non-technical colleagues.
• Ability to deliver reliable systems in complex data domains, manage multiple projects, reuse existing processes and services, and work with geographically dispersed colleagues.

Nice to have

• Strong Python and software-engineering practices, including version control, testing, and code review.
• Experience taking ML or data solutions from concept through production deployment and business adoption.
• Experience with ML engineering, scalable model serving, containerization, inference optimization, fine-tuning, distillation, and AI observability.
• Experience with agentic orchestration and multi-agent frameworks such as LangGraph or LangChain, tool and API integration, and secure agent connectivity.
• Experience with scalable data pipelines, SQL and NoSQL stores, distributed processing, vector databases, retrieval systems, AWS or Azure, Databricks, Git, and CI/CD.
• Experience with secure auditable systems, PHI/PII handling, data residency, and external partner integrations through APIs or secure data exchange.
• Familiarity with the U.S. healthcare and pharmaceutical landscape, or the ability to ramp quickly in a regulated domain; healthcare or pharma experience is a plus.

Culture & Benefits

• Purpose-driven technology work supporting medicine development, patient access, affordability, and outcomes.
• Full-time regular employment with potential company bonus based partly on company and individual performance.
• Benefits may include 401(k), pension, vacation, medical, dental, vision, prescription drug, flexible spending, life insurance, leave, well-being, fitness, and employee club programs.
• Work includes collaboration across Technology at Lilly, business, field, commercial, data science, and partner organizations.