AI Automation Engineer

🕒 June 18

🇺🇸 United States – Remote

💵 $130.3k - $195.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 QA Automation Engineer

👻 Ghost score 45%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Alignment Health

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2013

⚕️ Healthcare Insurance

🛡️ Insurance

🏥 Healthcare

💰 $135M Series C on 2020-03

Healthcare Insurance • Insurance • Healthcare

Alignment Health is dedicated to providing comprehensive care for Medicare members, emphasizing the needs of seniors, the chronically ill, and those who are frail. With a mission to transform senior healthcare, Alignment Health leverages a tailored care model and advanced technology to deliver high-quality, low-cost healthcare services. Their 24/7 concierge care team collaborates with trusted local providers to ensure that every member receives personalized care, reflecting the company's commitment to treating all members as valued family members.

📋 Description

• Design, build, and deploy intelligent AI systems and automated workflows for healthcare operations • Build distributed, cloud-native services, APIs, and microservices for enterprise workloads • Build hybrid integrations with flat files, legacy databases, EDI feeds, mainframes, streaming data, documents, images, and audio • Containerize and deploy systems using Docker and Kubernetes • Build CI/CD pipelines and apply infrastructure-as-code practices • Build ETL and orchestration pipelines using Airflow or Prefect • Automate high-volume processes using RPA platforms such as UiPath or Power Automate • Build and serve batch, real-time, and streaming inference pipelines • Integrate LLMs using prompt engineering, RAG, and agentic frameworks • Support Databricks, Delta Lake, MLflow, and Unity Catalog productionization • Build monitoring, alerting, and drift detection systems • Partner with AI Scientists, Product Managers, clinical stakeholders, and business analysts • Contribute to code reviews and documentation and provide informal technical mentorship • Operate as an individual contributor with no direct supervisory responsibility

🎯 Requirements

• 3–5 years of professional experience in software engineering with a demonstrated focus on AI/ML, data science, or intelligent process automation • Hands-on experience building and deploying machine learning models in a production cloud environment (AWS, Azure, or GCP) • Experience integrating systems with non-API and multimodal data sources • Experience in a regulated industry (healthcare, insurance, or financial services) • Hands-on experience applying AI/ML models or LLMs in a production system (integration/serving, not necessarily training) • Bachelor's degree in Computer Science, Engineering, Mathematics, Data Science, or a related quantitative field • Equivalent combination of education and demonstrated, progressive hands-on experience will be considered • Demonstrated proficiency with Python and ML frameworks through professional work experience; formal training or self-directed equivalent accepted • Working knowledge of cloud AI/ML services (AWS SageMaker, Azure AI, or Google Vertex AI); training or certification equivalent accepted • Proficiency in Python, PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers • Experience with LLM frameworks, RAG pipelines, vector databases, and agentic frameworks such as LangChain or LangGraph • Hands-on experience with at least one RPA platform (UiPath, Power Automate, Automation Anywhere) and one orchestration tool (Apache Airflow, Prefect, or n8n) • Hands-on experience with AWS SageMaker, Azure AI / Document Intelligence, Google Cloud Vertex AI, or Databricks • Familiarity with Docker, Kubernetes, and CI/CD pipelines for ML workflows • Ability to build and maintain ETL and feature pipelines • Proficiency with GitHub and model versioning tools such as MLflow or equivalent • Working knowledge of SQL for data transformation and workflow support • Working knowledge of HIPAA compliance and data security requirements in regulated healthcare environments • Familiarity with healthcare data standards including HL7 FHIR and ICD-10/CPT • Experience integrating AI models and automation services into enterprise applications via REST APIs and microservices • Awareness of and commitment to ethical AI practices • Ability to perform the stated essential physical functions, with reasonable accommodations available