Senior AI Automation Engineer - Alignment Health

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.

Job Duties / Responsibilities

Architect and deliver production-grade AI and machine learning systems. Lead the end-to-end design and deployment of predictive and generative AI models — including NLP, classification, regression, and computer vision — for high-stakes Medicare Advantage workloads. Own architectural decisions related to model selection, scalability, and production readiness, andestablishmonitoring and drift detection standards adopted across the team.

Lead the design and scaling of intelligent process automation. Evaluate and architect enterprise-wide automation strategies using RPA platforms (e.g., UiPath, Power Automate) and orchestration tools (e.g., Airflow, Prefect). Drive automation ROI analysis,establishengineering standards for fault-tolerant workflow design, and serve as the senior technical owner for the organization's most complex automation pipelines.

Own AI/ML data infrastructure strategy and pipeline reliability. Design and govern robust ETL and feature engineering pipelines that support model training,validation, and real-time inference at scale. Define infrastructure standards for experimentation, retraining, and monitoring that ensure consistent model performance across a regulated, high-availability production environment.

Integrate AI and automation systems into enterprise architecture. Lead the integration of deployed models and automation services into enterprise products via REST APIs and microservices,settingthe engineering bar for security, HIPAA compliance, and maintainability. Drive adoption of containerization (Docker, Kubernetes) and CI/CD best practices across the AI engineering team.

Architect and implement LLM-powered and agentic AI applications. Define the technical approach for integrating large language models into clinical and operational workflows — including prompt engineering, fine-tuning, RAG pipelines, and multi-agent orchestration frameworks (LangChain,LangGraph,AutoGen). Own delivery of agentic AI solutions that transform end-to-end workflows in areas such as clinical document intelligence, intelligent prior authorization, and member communication.

Establish reliability standards and drive continuous system improvement. Own the performance, reliability, andscalability postureof AI and automation sys