Artificial Intelligence Data Engineer II

LA Care Health Plan
Los Angeles, CA, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$105,267.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Cloud Computing Continuous Delivery Continuous Integration Information Engineering Data Governance DevOps Python (Programming Language) Machine Learning Meta-Data Management
+28 more
Natural Language Processing Performance Tuning Scrum Methodology Recommender Systems Azure Machine Learning Sentiment Analysis SQL Databases Data Streaming Data Processing Cloud Platform System Feature Engineering Data Ingestion Informatica Powercenter Fast Healthcare Interoperability Resources Snowflake Prompt Engineering Apache Spark Model Validation Git Information Technology Data Lineage AWS Glue Health Level Seven International Data Management Machine Learning Operations Data Delivery Software Version Control Data Pipelines

Job description

The 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.

Duties

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.

Requirements

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 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.

Preferred:

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.

Skills

Required:

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.

Preferred:

Experience with FHIR, HL7, HIPAA compliance, and healthcare data standards.

Licenses/Certifications Required

Licenses/Certifications Preferred

AWS Certified Data Engineer

Snowflake SnowPro Advanced

Certification in GenAI

Certification in MLOps Platforms

Required Training

Required:

Data pipeline development and cloud platform training.

Preferred:

Healthcare compliance and regulatory training.

Benefits & conditions

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)

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on juju.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

55 sec

Validating data processing architectures via containerized events

Modood Alvi · WWC 2025

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · WWC Europe 2026

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

3:18 min

Scaling global network engineering through DevOps culture

Stuart Clark · LIVE

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

Videos

See all

Related articles

See all