Head of Data and AI Platforms

Job Summary The Head of Data & AI Platforms leads the engineering organization responsible for building and operating the foundation that enables AI to transform healthcare at Medline. This role owns the enterprise data and AI platforms that power how the company generates, scales, and operationalizes insight and intelligence.

This is a deeply technical leadership role focused on taking an already strong data platform to the next level—evolving it into a unified, production-grade Data + AI platform that supports modern AI, including machine learning, generative AI, and emerging agentic patterns at enterprise scale. The role ensures that every AI and data product at Medline is built on a reliable, scalable, and reusable foundation—driving speed, quality, and consistency across the enterprise.

Job Description MAJOR RESPONSIBILITIES: Platform Ownership Own the enterprise Data and AI Platforms, including the roadmap, architecture, and engineering best practices. Evolve Medline’s existing data platform into a unified Data + AI platform that supports ML, GenAI, and emerging AI application patterns. Establish the platform as a shared, reusable foundation that scales across all domains and use cases. Modernize and extend the platform to support real-time data, large-scale model inference, and next-generation AI workloads.

Data, AI & MLOps Engineering Leadership Lead Data Engineering, ML/AI Platform (MLOps), and AI Platform engineering as a single, high-performing organization. Build and scale a world-class engineering team with strong depth in distributed systems, data platforms, and production AI. Standards, Quality & Production Readiness Define and enforce engineering standards, platform guardrails, and production readiness criteria. Ensure the platform is secure, reliable, and cost-efficient by design.

Establish SLAs and operational excellence practices to run the platform as a high-availability service. Operating Model & Ways of Working Design the platform to be the fastest and easiest path for teams to build and deploy data and AI products. Drive adoption through strong developer experience, tooling, and self-service capabilities. Establish clear onboarding pathways and support models for enterprise teams. Outcomes & Operational Excellence Improve time-to-production for AI and data products across the enterprise.

Increase the number and scale of models and data products running reliably in production. Continuously optimize platform cost, performance, and developer productivity.

Platform Run / Operations Manage teams that monitor the platform and be accountable for monitoring, service levels on availability, and incident management Establish SLAs, availability standards, monitoring requirements, and operational governance Provide executive oversight of major incidents, coordinated recovery, and corrective actions that reduce recurring issues and drive resolutions through automation, self-service and knowledge management. MINIMUM JOB REQUIREMENTS Education Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.

Certification / Licensure No specific certification or licensure required. Work Experience 15+ years of experience in engineering leadership across data platforms, distributed systems, or AI/ML infrastructure. Proven track record of building and scaling enterprise-grade data or AI platforms. Knowledge / Skills / Abilities Deep hands-on understanding of modern cloud data platforms (Databricks, Microsoft Fabric, or equivalent). Strong experience with MLOps and production AI systems (model serving, feature stores, monitoring, lifecycle management).

Demonstrated ability to lead engineering teams and deliver highly scalable, reliable platforms. Strong platform-as-a-product mindset — shared services, SLAs, and reuse over rebuild. Strong bias for outcomes — platform uptime, cost, and time-to-production over artifacts. PREFERRED JOB REQUIREMENTS Education Master’s degree in Computer Science, Engineering, or a related technical field. Certification / Licensure Relevant cloud, data platform (Databricks / Azure), or MLOps credentials. Work Experience Prior experience leading large remote / India / offshore engineering teams.

Experience delivering an enterprise-wide Data + AI platform from the ground up. Knowledge / Skills / Abilities Experience evolving an existing data platform into a modern Data + AI platform. Familiarity with GenAI, LLM platforms, and emerging agentic architectures. Experience operating shared platforms with SLAs and internal customer models. Experience leading global engineering teams, including offshore models. Strong track record of improving engineering velocity and platform adoption at scale.

Familiarity with Azure Data Factory, Azure Data Lake, Databricks, Azure Synapse, Microsoft Fabric and/or Power BI is preferred. DISCLAIMER All duties and requirements are subject to possible modification to reasonably accommodate individuals with disabilities. This position description in no way states or implies that these are the only duties to be performed by an employee occupying this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by their supervisor(s)/manager(s).

This document does not create an employment contract, implied or otherwise, other than an "at will" employment relationship. Click here to learn more about a career in IT at Medline! Medline Industries, LP, and its subsidiaries, offer a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization. The anticipated salary range for this position: $203,000.00 - $305,000.00 Annual The actual salary will vary based on applicant’s location, education, experience, skills, and abilities.

Medline will not pay less than the applicable minimum wage or salary threshold. Our benefit package includes health insurance, life and disability, 401(k) contributions, paid time off, etc., for employees working 30 or more hours per week on average. For a more comprehensive list of our benefits please click here. For roles where employees work less than 30 hours per week, benefits include 401(k) contributions as well as access to the Employee Assistance Program, Employee Resource Groups and the Employee Service Corp.

We’re dedicated to creating a Medline where everyone feels they belong and can grow their career. We strive to do this by seeking diversity in all forms, acting inclusively, and ensuring that people have tools and resources to perform at their best. Explore our Belonging page here. Medline Industries, LP is an equal opportunity employer.

Medline evaluates qualified individuals without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, age, disability, neurodivergence, protected veteran status, marital or family status, caregiver responsibilities, genetic information, or any other characteristic protected by applicable federal, state, or local laws. Through our culture of belonging, our agile and resilient global team is determined to get our customers exactly what they need, at the right time, every time.

If you’re a self-starter, eager to grow your career within a high-performing environment, this is the place for you. Introduce yourself to our recruiters and we'll get in touch if there's a role that seems like a good match. Medline is the largest provider of medical-surgical products and supply chain solutions serving all points of care. Through its broad product portfolio, resilient supply chain and leading clinical solutions, Medline helps healthcare providers improve their clinical, financial and operational outcomes.

Headquartered in Northfield, Illinois, the company employs more than 43,000 people worldwide and operates in more than 100 countries and territories. To learn more about how Medline makes healthcare run better, visit www.medline.com.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• 15+ years engineering leadership in data platforms, distributed systems, or AI/ML infrastructure
• Deep hands-on experience with cloud data platforms, MLOps, and production AI systems