Data Engineer with AI/ML

Primary Responsibilities

• Design and develop AI-driven solutions using LLMs to automate claims adjudication processes
• Build and optimize prompt engineering strategies for LLM-based applications
• Implement and integrate agentic frameworks to enable autonomous decision-making workflows
• Architect and deploy scalable data pipelines and AI workflows leveraging Python and related technologies
• Collaborate with cross-functional teams to ensure compliance with healthcare data standards and Responsible AI principles
• Contribute to model development, evaluation, and fine-tuning for production environments
• Mentor junior engineers and foster knowledge-sharing within the team
• Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI

Required Qualifications

• Bachelor's degree in CS or IT related field
• 5+ years of hands-on experience in data engineering and backend automation
• 5+ years of experience in Python, PySpark (Databricks), T-SQL, SQL, and big data technologies (Hadoop, Spark)
• 5+ years of experience with ETL tools, workflow orchestration (Airflow), and data warehousing (Snowflake or similar)
• 1+ years of experience in any one of the cloud technologies like Azure (ML Studio), AWS, GCP
• 1+ years of experience with CI/CD pipelines, GitHub Actions, and containerization tools (Docker)
• 1+ years of experience with Agile methodologies and DevOps practices
• 6+ months of experience with Generative AI frameworks/architectures (LangChain, HuggingFace, OpenAI APIs)
• 6+ months of experience with AI/ML concepts including Generative AI, LLMs (GPT, Gemini, LLaMA), and prompt engineering

Preferred Qualifications

• Understanding of Responsible AI principles and engineering best practices
• Familiarity with healthcare or health insurance domain data and compliance standards
• Excellent problem-solving skills and ability to handle ambiguity