Note: The job is a remote job and is open to candidates in USA. Alignment Health is a healthcare company focused on serving seniors and people with chronic and complex health needs. The Principal Artificial Intelligence & Automation Engineer will define and execute the AI and automation strategy for the Medicare Advantage business, leading the delivery and scaling of compliant AI-powered systems and intelligent automation. The role will partner with clinical, financial, claims, product, compliance, and technology teams to improve care quality, member experience, payment accuracy, and operational performance.
Responsibilities
- 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 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
- 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
- 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
- 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
- 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
- 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
Skills
- 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
- 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
- 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
- **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 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
- 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
- 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)
- 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
Benefits
- Fully remote work
Company Overview
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