Gen AI Engineer: Enterprise Data & ML Pipelines

Sedgwick; Tennessee; On-site; USD 120,000 - 180,000; Full time

Job summary

Sedgwick is seeking a Gen AI Engineer to architect enterprise data supply chains, building production-grade pipelines for analytics, ML, and AI initiatives. You’ll curate data for ML models, feature stores, and gen AI applications across multi-cloud environments.

The role emphasizes data quality, orchestration, and collaboration with Data Science and MLOps teams to deliver scalable, reliable data solutions.

Qualifications

• Master’s degree in Computer Science, Data Engineering, or a related field preferred.
• Six (6) years of hands-on data engineering experience building production-grade pipelines for Data Science and AI in multi-cloud environments.
• Experience with Snowflake power user concepts and data modeling patterns is essential.
• Strong knowledge of Python, SQL, PySpark, and data orchestration technologies.

Responsibilities

• Designs, builds, and maintains resilient ETL/ELT pipelines ingesting data from on‑premise systems, AWS, and Azure.
• Develops feature stores and datasets for machine learning workflows with clean, versioned data.
• Constructs pipelines for generative AI use cases; loads data into vector databases across AWS and Azure.
• Acts as Snowflake power user; optimizes compute/storage and automates Snowpipe for high concurrency.

Skills

Snowflake

AWS

Azure

Python

SQL

PySpark

Docker

Data orchestration

Education

Master’s degree in Computer Science, Data Engineering, or a related field

Tools

Docker

Job description

Sedgwick is seeking a Gen AI Engineer to architect enterprise data supply chains, building production-grade pipelines for analytics, ML, and AI initiatives. You’ll curate data for ML models, feature stores, and gen AI applications across multi-cloud environments.

The role emphasizes data quality, orchestration, and collaboration with Data Science and MLOps teams to deliver scalable, reliable data solutions.