Artificial Intelligence Data Engineer II

L.A. Care Health Plan•Los Angeles, CA

7d•$105,267 - $173,689

About The Position

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, we make sure our members get 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. Job SummaryThe Artificial Intelligence Data Engineer II designs, develops, and manages scalable data pipelines and feature stores that enable AI/Machine Learning (ML) model training and deployment across the enterprise. This position collaborates with technical team members to automate data flows, integrate structured and unstructured data sources, and optimize performance for large-scale processing. The AI Data Engineer II also implements data quality validation, metadata management, and lineage tracking to ensure trusted data delivery for AI applications in compliance with healthcare regulations.DutiesDesign 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 Health Insurance Portability and Accountability Act (HIPAA), Centers for Medicare and Medicaid Services (CMS), and enterprise data governance standards. Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and Informatica Data Management Cloud (IDMC). Implement DevOps/MLOps and Continuous Integration (CI)/Continuous Delivery (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.Duties Continued

Requirements

At least 5 years of experience in data engineering.
At least 2 years of experience focused on AI/ML data pipelines.
Hands on experience working on GenAI projects (chatbot implementations, Natural Language Processing (NLP), Sentiment Analysis, recommendation systems, anomaly detection etc.
Proficient skills in Python, SQL, Spark, AWS (Glue, S3, Lambda), Snowflake (Snowpark Container Services), IDMC, prompt engineering, model inference and fine-tuning, RAG and working with MCP, Vector databases.
Proficient technical and data engineering skills
Solid understanding of supervised and unsupervised machine learning methods, feature engineering, model evaluation, and validation techniques.
Ability to operationalize models in production environments, including basic MLOps practices (version control, CI/CD, reproducibility).
Ability to communicate complex AI/ML concepts effectively to non-technical stakeholders.
Excellent documentation skills, ensuring reproducibility, clarity of assumptions, and transparency of model design.
Strong collaboration skills, with proven ability to work cross-functionally with key stakeholders.
Analytical problem-solving skills with the ability to translate business challenges into actionable AI/ML solutions.
Effective written and verbal communication skills, including documentation of modeling processes, assumptions, and results.
Bachelor's Degree in Computer Science or Related Field In lieu of degree, equivalent education and/or experience may be considered.
Data pipeline development and cloud platform training.

Nice To Haves

Experience in health plan payer systems and regulatory data handling.
Experience with Fast Healthcare Interoperability Resources (FHIR), Health Level Seven (HL7), HIPAA compliance, and healthcare data standards.
Experience with FHIR, HL7, HIPAA compliance, and healthcare data standards.
Master's Degree in Data Science or Related Field
AWS Certified Data Engineer
Snowflake SnowPro Advanced
Certification in GenAI
Certification in MLOps Platforms
Healthcare compliance and regulatory training.

Responsibilities

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 Health Insurance Portability and Accountability Act (HIPAA), Centers for Medicare and Medicaid Services (CMS), and enterprise data governance standards.
Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and Informatica Data Management Cloud (IDMC).
Implement DevOps/MLOps and Continuous Integration (CI)/Continuous Delivery (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.