Artificial Intelligence Data Engineer II

Overview

Salary Range: $ (Min.) - $ (Mid.) - $ (Max.)

Established in 1997, L.A. Care Health Plan is an independent public agency created by the state of California to provide health coverage to low-income Los Angeles County residents. We are the nation’s largest publicly operated health plan, serving more than 2 million members and ensuring members receive the right care at the right place at the right time.

Mission: L.A. Care’s mission is to provide access to quality health care for Los Angeles County's vulnerable and low-income communities and residents and to support the safety net required to achieve that purpose.

• Design and implement scalable data pipelines for AI/ML workloads.
• Develop and deploy AI/ML solutions using Python, Snowpark, or cloud-native ML services.
• Build and manage feature stores to support model training and inference.
• Integrate structured and unstructured data sources from internal and external systems.
• Collaborate with data scientists to understand data requirements and optimize pipelines.
• Implement data quality checks, metadata tagging, and lineage tracking.
• Ensure compliance with HIPAA, CMS, and enterprise data governance standards.
• Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and IDMC.
• Implement Dev Ops/MLOps and CI/CD pipelines using Git actions or similar tools.
• Monitor pipeline performance and troubleshoot issues in production environments.
• Contribute to backlog grooming and sprint planning for AI data initiatives.
• Perform other duties as assigned.

• Education Required: Bachelor's Degree in Computer Science or related field. In lieu of degree, equivalent education and/or experience may be considered.
• Education Preferred: Master's Degree in Data Science or related field.
• Experience
  
  Required:
  
  At least 5 years of experience in data engineering; at least 2 years focused on AI/ML data pipelines; hands-on experience with GenAI projects (e.g., chatbot implementations, NLP, sentiment analysis, recommendation systems, anomaly detection).
• Experience Preferred: Experience in health plan payer systems and regulatory data handling.
• Experience with: FHIR, HL7, HIPAA compliance, and healthcare data standards.

• Required: Proficient in Python, SQL, Spark, AWS (Glue, S3, Lambda), Snowflake (Snowpark Container Services), IDMC; experience with prompt engineering, model inference and fine-tuning, RAG, and working with MCP; vector databases.
• Strong data engineering fundamentals and ability to operationalize models in production (basic MLOps, version control, CI/CD, reproducibility).
• Ability to communicate complex AI/ML concepts to non-technical stakeholders; excellent documentation to ensure reproducibility and transparency.
• Strong collaboration and cross-functional teamwork; analytical problem-solving; clear written and verbal communication of modeling processes, assumptions, and results.
• Preferred: Experience with healthcare data standards (FHIR, HL7) and HIPAA compliance.

• Licenses/Certifications Preferred: AWS Certified Data Engineer;
  Snowflake Snow Pro Advanced;
  Certification in GenAI;
  Certification in MLOps Platforms.

• Required Training: Data pipeline development and cloud platform training.
• Preferred Training: Healthcare compliance and regulatory training.

Light

Salary Range Disclaimer: The expected pay range is based on many factors such as geography, experience, education, and the market. The range is subject to change.

• Paid Time Off (PTO)
• Tuition Reimbursement
• Retirement Plans
• Medical, Dental and Vision
• Wellness Program
• Volunteer Time Off (VTO)