Director, AI & Automation Engineering

About the role

The Director, AI & Automation Engineering (remote) is a senior technology leader responsible for defining and executing the enterprise AI and automation strategy that powers our Medicare Advantage business.

Responsibilities

• Set AI & automation strategy aligned to Medicare Advantage priorities.
  • Define and maintain a multi-year AI and automation roadmap that supports strategic goals in Stars, risk adjustment, payment accuracy, prior authorization, clinical quality, and member experience.
  • Partner with C-suite and senior leaders to identify and prioritize high-ROI use cases where AI and intelligent automation create durable competitive advantage.
• Lead and develop a high-performing AI & Automation Engineering team.
  • Build, lead, and retain a diverse team of AI/ML engineers, automation engineers, and related roles, setting clear goals, expectations, and development plans.
  • Foster a culture of talent density, accountability, and continuous learning — using data-driven performance management and succession planning to grow future technical leaders.
• Drive enterprise-scale intelligent automation.
  • Lead the design and implementation of enterprise-grade automation solutions — including RPA, workflow orchestration, and process intelligence — across functions such as Claims, UM, Provider Operations, and Member Services.
  • Establish standards and governance for automation development, documentation, and change management to ensure scalability and maintainability.
  • Establish platforms, tooling, and engineering best practices.
  • Own the selection and adoption of AI/ML platforms, cloud services (AWS/Azure/GCP), and automation tools (e.g., UiPath, Power Automate), ensuring they integrate with DTS data platforms and security controls.
  • Define and enforce engineering best practices — CI/CD, MLOps, testing, observability, and documentation — that raise the bar for reliability and time-to-value across all AI and automation initiatives.
  • Partner cross-functionally to deliver measurable business impact.
• Embed responsible AI and regulatory compliance.
  • Work with Legal, Compliance, and Privacy to ensure all AI and automation solutions meet CMS, HIPAA, and internal governance standards.
  • Implement frameworks for bias detection, model explainability, auditability, and change control, recognizing that AI outputs directly influence member care decisions and financial outcomes.
• Manage budget, vendors, and external partnerships.
  • Own the operating budget for AI & Automation Engineering, including cloud spend, third-party platforms, and external partners.
  • Evaluate and manage vendor relationships to ensure investments reflect labor market realities and maximize ROI.

Requirements

• 8–12 years of progressive experience in software engineering, data science, or AI/ML roles, with at least 3–5 years in a senior leadership or director-level position.
• Proven track record of delivering production-grade AI/ML systems and large-scale automation solutions in a regulated or enterprise environment.
• Demonstrated experience leading and scaling multi-disciplinary engineering teams, including hiring, performance management, and career development.
• Deep expertise in machine learning, NLP, generative AI (LLMs, RAG pipelines), agentic frameworks, and intelligent process automation (RPA and orchestration).

Qualifications

• Bachelor's degree in Computer Science, Computer & Electrical Engineering, Mathematics, Data Science, or a related quantitative field.
• Master's degree or PhD in Computer Science, AI/ML, or a related quantitative discipline.

Skills & Competencies

• Technical / Role-Specific Skills:
  • AI/ML Strategy & Technical Governance: Deep, hands-on understanding of the full AI/ML lifecycle — model design, training, deployment, monitoring, and MLOps — with the ability to set organizational standards, make high-stakes platform decisions, and guide senior engineers through complex technical challenges.
  • Intelligent Automation Leadership: Proven ability to define and govern enterprise automation strategy using RPA platforms (UiPath, Power Automate, Automation Anywhere) and orchestration tools (Airflow, Prefect); experience establishing automation governance frameworks, ROI accountability, and cross-functional program leadership.
  • Cloud AI Platform Ownership: Expert-level familiarity with AWS SageMaker, Azure AI / Document Intelligence, Google Cloud Vertex AI, or Databricks; experience owning platform selection, cost governance, and architecture standards at a department level.
  • Engineering Leadership & Talent Development: Demonstrated ability to build, scale, and retain high-performing AI engineering teams; strong track record in performance management, succession planning, and cultivating a culture of technical excellence and continuous learning.
  • Healthcare Domain & Regulatory Expertise: Deep working knowledge of HIPAA, CMS regulations, and data governance in regulated healthcare environments; advanced fluency in healthcare AI use cases including risk adjustment, payment integrity, clinical NLP, and member engagement.
• Executive Communication & Stakeholder Influence: Ability to translate complex AI and automation strategy into clear executive narratives; experience presenting to boards, C-suite, and governance bodies; demonstrated success influencing senior decision-making through data, business outcomes, and technical credibility.
• Responsible AI & Governance: Applied leadership experience with ethical AI frameworks including bias detection, model explainability (SHAP, LIME, or equivalent), auditability, and responsible AI program design; ability to embed governance standards organization-wide in a high-stakes healthcare context.

Pay

$172,364.00 - $258,547.00