Director, AI Platform & Transformation

Career-defining. Life-changing.

At iRhythm, you’ll have the opportunity to grow your skills and your career while impacting the lives of people around the world. iRhythm is shaping a future where everyone, everywhere can access the best possible cardiac health solutions. Every day, we collaborate, create, and constantly reimagine what’s possible. We think big and move fast, driven by our commitment to put patients first and improve lives. We need builders like you. Curious and innovative problem solvers looking for the chance to meaningfully shape the future of cardiac health, our company, and your career

About This Role:

Career-defining. Life-changing.

iRhythm is creating a healthier future through innovative cardiac care. Our Data, Analytics & AI organization is building governed platforms, data products, and intelligent workflows that help our teams make better decisions and deliver more value.

About This Role

The Director, AI Platform & Transformation will lead iRhythm’s enterprise AI strategy across platform, technology, business transformation, and adoption. This role will move AI from experimentation into secure, scalable, measurable production use.

You will combine executive leadership with hands-on technical depth, partnering with business leaders, Data and Engineering, IT, Security, Privacy, Legal, Compliance, Quality, and Finance.

What You Will Be Doing

• Define the AI platform and transformation roadmap, aligned to business priorities and measurable outcomes.
• Prioritize AI opportunities across Clinical Operations, Commercial, Finance, Customer Care, Manufacturing, Quality, R&D, and enterprise functions.
• Lead initiatives from discovery through production launch, adoption, and continuous improvement.
• Architect and scale AI applications and platforms using generative AI, LLMs, RAG, agents, workflow orchestration, and model evaluation.
• Partner with Data Platform and Engineering to make governed data products, semantic definitions, metadata, lineage, and data quality usable by AI systems.
• Establish standards for reliability, autoscaling, performance, security, privacy, testing, monitoring, observability, incident response, lifecycle management, and cost control.
• Build business cases, value-realization plans, governance playbooks, and executive reporting.
• Lead and grow teams and strategic vendor partnerships while driving AI literacy and adoption across the organization.

Technology Environment

Our environment spans the enterprise AI and data stack. Experience with every named technology is not required.

• AI and agents: Glean, LLMs, LangChain, LangGraph, RAG, workflow orchestration, model evaluation, MLflow, AWS Bedrock, vLLM, Ray, Model Context Protocol (MCP), Langfuse, prompt management, guardrails, and human-in-the-loop workflows.
• Data and analytics: Snowflake, Snowflake Cortex, Databricks, PySpark, Spark Structured Streaming, PyTorch, Scala, FastAPI, semantic views, governed data products, Tableau, Retool, data quality, metadata, cataloging, and lineage.
• Cloud and integration: AWS, Azure, APIs, CI/CD, observability, Alation, OAuth/SSO, and integrations with Jira, Confluence, GitLab, Salesforce, QAD, Workday, Microsoft 365, SharePoint, and Teams.

Required Qualifications

• 7+ years of experience building and scaling AI software products serving audiences ranging from thousands to millions of users.
• Experience designing and operating large-scale machine learning infrastructure, including autoscaling, reliability, and production performance optimization.
• 4+ years of experience building AI and generative AI systems, including developing AI models, fine-tuning LLMs, evaluating model quality, deploying and productionizing LLM applications, and monitoring them in enterprise environments.
• 3+ years of hands-on experience building AI applications and platforms using LLMs, LangChain, LangGraph, RAG, workflow orchestration, MLflow, and AWS Bedrock.
• 3+ years of experience as the owner of an applied AI product domain, such as real-world data, agentic environments, evaluation, or multimodal and multilingual ML, where you drove significant business outcomes.
• Hands-on experience deploying and operating AI systems using vLLM, Ray, the Model Context Protocol (MCP), and Langfuse.
• 7+ years of professional experience with Python and strong experience with PySpark, Spark Structured Streaming, PyTorch, Scala, and FastAPI.
• Demonstrated experience …