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Alignmenthealthcare

Principal AI & Automation Engineer

Anywhere in the U.S.

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hirly's read of this role

Seniority
Lead / management
Country
US
Work mode
Remote-friendly
First seen by hirly
30 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most: the chronically ill and frail. It takes an entire team of passionate and caring people, united in our mission to put the senior first. We have built a team of talented and experienced people who are passionate about transforming the lives of the seniors we serve. In this fast-growing company, you will find ample room for growth and innovation alongside the Alignment Health community. Working at Alignment Health provides an opportunity to do work that really matters, not only changing lives but saving them. Together.

The Principal Artificial Intelligence & Automation Engineer is a senior subject matter expert responsible for defining and executing the AI and automation strategy that powers Alignment Health’s Medicare Advantage business. This role will design, deliver, and scale AI-powered systems and intelligent automation that improve care quality, member experience, and operational performance. Partnering closely with DTS leadership, Clinical Operations, Finance, Claims, and Product, this role will identify the highest-value AI and automation opportunities, translate them into a cohesive roadmap, and ensure reliable, compliant delivery in a highly regulated environment. This role is pivotal in shaping how Alignment applies cutting-edge AI and automation to reduce administrative burden, drive payment accuracy, and unlock zero wasted potential in how work gets done across the organization.

Job Duties/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.

Drive 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, including 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

  • Collaborate with Product, Data Engineering, Clinical Operations, Finance, Compliance, and Security to translate business requirements into technical solutions and track realized value (e.g., cycle time reduction, accuracy improvement, cost-to-serve).
  • Regularly communicate AI and automation strategy, progress, and ROI to senior executives and governance bodies.

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.

Supervisory Responsibilities

This role has no direct reports or people-management responsibilities. It provides technical leadership, mentoring, and cross-functional direction through expertise and influence rather than supervisory authority.

Job Requirements

EXPERIENCE

Required:

  • 8–12 years of progressive experience in software engineering, data science, or AI/ML roles, with at least 3–5 years in a senior level position.
  • Proven track record of delivering production-grade AI/ML systems and large-scale automation solutions in a regulated or enterprise environment.
  • Deep expertise in machine learning, NLP, generative AI (LLMs, RAG pipelines), agentic frameworks, and intelligent process automation (RPA and orchestration).
  • Experience managing budgets, vendor relationships, and technology platform decisions at a department or function level.

Preferred:

  • Experience in healthcare, specifically Medicare Advantage, managed care, or payer environments, with fluency in use cases such as risk adjustment, prior authorization, claims processing, Stars ratings, and revenue cycle management.
  • Demonstrated knowledge of healthcare data standards including HL7 FHIR, ICD-10/CPT, or DICOM as applied to AI systems.
  • Track record of building and scaling an AI or automation engineering function from early stage to enterprise maturity.
  • Published research, conference presentations, or demonstrated thought leadership in AI/ML or enterprise automation.

EDUCATION

Required:

Bachelor's degree in Computer Science, Computer & Electrical Engineering, Mathematics, Data Science, or a related quantitative field.

Equivalent combination of education and demonstrated experience will be considered.

Preferred:

  • Master's degree or PhD in Computer Science, AI/ML, or a related quantitative discipline.
  • Advanced or specialty cloud certification from AWS, Microsoft Azure, or Google Cloud (AI/ML, data, or architecture track).
  • RPA platform certification at an advanced or architect level (UiPath, Automation Anywhere, or Microsoft Power Automate).

TRAINING

Required:

Demonstrated senior-level proficiency with AI/ML engineering practices, cloud platforms, and enterprise automation through professional experience; formal training or equivalent self-directed mastery accepted.

Working knowledge of cloud AI/ML governance and platform management (AWS, Azure, or GCP) at a leadership level; certification or equivalent experience accepted.

Preferred:

  • Executive or senior-level certification or coursework in AI strategy, responsible AI governance, MLOps, or cloud AI platforms.
  • Certification in RPA platforms (UiPath, Automation Anywhere, or Microsoft Power Automate) or advanced MLOps tooling.
  • Participation in AI/ML industry bodies, advisory boards, or standards organizations

SPECIALIZED SKILLS

  • AI/ML Strategy & Technical Governance: Deep, hands-on understanding of the full AI/ML lifecycle, including 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.
  • 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 engag
Original posting on Alignmenthealthcare's site ↗

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