Senior AI Automation Engineer

Alignment Health is breaking the mold in conventional health care, committed to serving seniors and those who need it most. The Senior AI & Automation Engineer will architect, build, and scale intelligent AI systems and enterprise automation solutions to improve care quality and operational performance across the Medicare Advantage business.

Responsibilities:

• Architect and deliver production-grade AI and machine learning systems
• Lead the design and scaling of intelligent process automation
• Own AI/ML data infrastructure strategy and pipeline reliability
• Integrate AI and automation systems into enterprise architecture
• Architect and implement LLM-powered and agentic AI applications
• Establish reliability standards and drive continuous system improvement
• Mentor engineers and shape AI engineering culture

Requirements:

• 5–8 years of professional experience in software engineering with a demonstrated, progressive focus on AI/ML, data science, or intelligent process automation
• Proven track record of independently owning and delivering complex, production-grade AI/ML systems from design through deployment and ongoing operations
• Demonstrated experience with the full AI/ML model lifecycle at scale: data architecture, model design, training, validation, deployment, monitoring, and retraining
• Experience in a regulated industry (healthcare, insurance, or financial services) with deep working knowledge of compliance and security requirements in production AI environments
• Experience architecting and scaling automation solutions using RPA platforms and workflow orchestration tools, including cross-functional stakeholder engagement and ROI governance
• Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related quantitative field
• Equivalent combination of education and demonstrated, progressive senior-level hands-on experience will be considered
• Advanced, demonstrated proficiency with Python and ML frameworks through professional work experience at a senior level; formal training or equivalent self-directed mastery accepted
• Hands-on experience with cloud AI/ML platforms (AWS SageMaker, Azure AI, or Google Vertex AI) at an architecture or senior engineering level; certification or equivalent experience accepted
• AI/ML Engineering: Expert-level Python proficiency with deep command of ML frameworks including PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers; advanced experience designing LLM-based systems including RAG pipelines, vector databases, and multi-agent orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI)
• Intelligent Process Automation — Architecture & Governance: Proven ability to architect enterprise-scale automation strategies using RPA platforms (UiPath, Power Automate, Automation Anywhere) and orchestration tools (Apache Airflow, Prefect, or n8n); experience setting engineering standards, conducting automation ROI governance, and leading complex, cross-functional automation programs
• Cloud AI Platforms & MLOps: Expert-level experience with AWS SageMaker, Azure AI / Document Intelligence, Google Cloud Vertex AI, or Databricks; mastery of containerization (Docker, Kubernetes), CI/CD pipelines, and MLOps tooling (MLflow, Kubeflow, or equivalent) at an architecture and governance level
• Data Engineering & AI Infrastructure: Ability to design, govern, and scale ETL and feature pipelines across complex, high-availability healthcare environments; deep proficiency in SQL, data architecture patterns, and real-time inference infrastructure
• Healthcare & Regulatory Expertise: Deep working knowledge of HIPAA compliance, data security requirements, and data governance in regulated healthcare environments; advanced familiarity with healthcare data standards including HL7 FHIR and ICD-10/CPT as applied to production AI and automation systems
• Technical Leadership & AI Innovation: Demonstrated ability to drive architectural decisions, mentor engineers, lead design reviews, and shape engineering standards across a team; track record of identifying and delivering high-ROI AI and automation innovations in an enterprise healthcare context
• Responsible AI & Governance: Applied experience with ethical AI frameworks including bias detection, model explainability (SHAP, LIME, or equivalent), and AI governance practices; ability to embed responsible AI standards into team workflows where AI outputs directly influence member care and financial decisions
• Experience applying AI, NLP, or ML to complex healthcare data including claims processing, revenue cycle management, prior authorization, medical coding, or clinical text understanding
• Demonstrated knowledge of healthcare data standards including HL7 FHIR, ICD-10/CPT codes, or DICOM
• Experience in a Medicare Advantage, managed care, or payer environment at a senior engineering level
• Prior experience as an informal technical lead, principal engineer, or engineering lead on an AI/ML team
• Master's degree in Computer Science, AI/ML, or a related quantitative discipline
• Formal certification or coursework in MLOps, cloud AI platforms (AWS, Azure, or GCP), responsible AI, or agentic AI development
• Certification in RPA platforms (UiPath, Automation Anywhere, or Microsoft Power Automate)
• Participation in advanced AI/ML communities, conferences, or open-source contributions demonstrating technical depth
• Cloud certification from AWS, Microsoft Azure, or Google Cloud at an advanced or specialty level (AI/ML or data engineering track)
• RPA platform certification (UiPath, Automation Anywhere, or Microsoft Power Automate)