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 chronically ill and frail. 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. The Senior AI & Automation Engineer is a senior individual contributor and technical leader on the Data & Technology Solutions team, responsible for architecting, building, and scaling intelligent AI systems and enterprise automation solutions that directly improve care quality and operational performance across our Medicare Advantage business. You will serve as a go-to technical expert for AI Scientists, Data Engineers, Product Managers, Clinical Operations, and Application Engineering teams — driving end-to-end delivery of production AI systems that span claims processing, risk adjustment, prior authorization, revenue integrity, and member engagement. This role carries a higher degree of independent ownership and technical authority than the mid-level equivalent, with expectations to lead complex, ambiguous initiatives from concept through production and to actively elevate the engineering practices of the broader team. Lead the build of distributed, cloud-native systems for enterprise workloads. Own the design and build of services, APIs, and microservices that run reliably at scale in a regulated environment. Lead hybrid infrastructure work bridging cloud and non-cloud systems. Own the build of integrations with non-API data sources, including flat files, legacy databases, EDI feeds, mainframes, and streaming data, as well as multimodal data such as documents, images, and audio. Own CI/CD, containerization, and deployment standards. Own data and automation pipeline reliability. Build and govern ETL and orchestration pipelines at scale. Own automation strategy using RPA platforms and orchestration tools, including ROI governance and engineering standards for fault-tolerant workflow design. Apply AI/ML to production systems and own inferencing performance (applied, not research). Own the build of inferencing pipelines (batch, real-time, streaming) that serve models handed off from AI Sciences, for workloads such as claims processing, risk adjustment, and member communication. Partner directly with AI Scientists to take models from research into low-latency, high-throughput production systems, owning the benchmarking and tuning that gets them there. This is applied integration, serving, and performance ownership, not model research or training. Own the technical approach for integrating LLMs into workflows, including prompt engineering, RAG, and multi-agent orchestration frameworks (LangChain, LangGraph, AutoGen). Lead the Databricks build-out supporting AI Sciences. Own productionizing models and pipelines built on Databricks, including Delta Lake, MLflow, and Unity Catalog. Own the CI/CD, orchestration, access controls, and cost tuning that let Databricks-based work move reliably into production, and set standards for how the team uses the platform. Mentor engineers and shape engineering culture. Contribute to hiring, technical interviews, and team-wide engineering standards, including responsible AI practices such as bias detection, explainability, and governance. Expected to function as an informal technical lead: mentoring, conducting code reviews, participating in hiring panels, and guiding the technical direction of junior and mid-level engineers on project teams. 5-8 years of professional software engineering experience with a demonstrated focus on distributed systems, cloud infrastructure, or data platforms

• Proven track record independently owning and delivering complex, production-grade distributed systems from concept through deployment and operations
• Experience building and scaling hybrid infrastructure connecting cloud-native and non-API/legacy systems
• Demonstrated experience serving and integrating AI/ML models or LLMs in production, including performance tuning (not model training/research)
• Experience in a regulated industry (healthcare, insurance, or financial services) with deep working knowledge of compliance and security requirements
• Experience building and scaling automation solutions using RPA platforms and workflow orchestration tools, including ROI governance

Experience with the Databricks platform (Delta Lake, MLflow, Unity Catalog) at a senior or platform-owner level

• Experience applying AI/ML to complex healthcare data (claims, revenue cycle, prior authorization, medical coding, clinical text)
• 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

Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or related quantitative field, or equivalent progressive senior-level experience ~ Master's degree in Computer Science or related quantitative discipline Advanced or specialty cloud certification (AWS, Azure, or GCP); RPA platform certification All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, gender identity, or sexual orientation. *Please beware of recruitment phishing scams affecting Alignment Health and other employers where individuals receive fraudulent employment-related offers in exchange for money or other sensitive personal information. If you feel that you have been the victim of a scam such as this, please report the incident to the Federal Trade Commission at If you would like to verify the legitimacy of an email sent by or on behalf of Alignment Health’s talent acquisition team, please email View email address on click.appcast.io.