AI Data Engineer: Scalable Pipelines for LLM/AI workloads

Capital One; Deerfield (IL); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One is seeking a Data Engineer to design and implement an AI-enabled data ecosystem, connecting traditional data architectures with modern AI workloads. You will build resilient, scalable pipelines supporting LLMs, RAG, and predictive ML models, while guiding engineers on standards and best practices.

You will partner with data scientists, analysts, and executives to deliver enterprise data products and decisioning engines, driving efficient data solutions across on‑prem and cloud

Qualifications

• Bachelor’s or higher in Computer Science or related quantitative field.
• At least 6 years of experience in application development.
• At least 4 years of experience with distributed data.
• At least 4 years of experience with SQL.
• At least 4 years of programming in Python, Java, or Scala.
• At least 4 years of experience designing and developing data pipelines.
• At least 2 years of experience in data modeling and end-to-end data solutions.

Responsibilities

• Architect, build, and scale data pipelines (batch and real-time) for AI/ML apps and LLMs.
• Lead architectural blueprint for the Top of House AI data layer and mentor engineers.
• Collaborate with Security and Data Governance for classification, privacy, and lineage.
• Build scalable feature stores for real-time inference and offline training.
• Audit and optimize cross-cloud data pipelines, queries, and storage.

Skills

SQL

Python

Java

Scala

Data pipelines

Distributed data

Education

Bachelor’s Degree in Computer Science or related field

Master’s Degree in a related field

Tools

Snowflake

AWS

Azure

Google Cloud

Claude

Gemini

Job description

Capital One is seeking a Data Engineer to design and implement an AI-enabled data ecosystem, connecting traditional data architectures with modern AI workloads. You will build resilient, scalable pipelines supporting LLMs, RAG, and predictive ML models, while guiding engineers on standards and best practices.

You will partner with data scientists, analysts, and executives to deliver enterprise data products and decisioning engines, driving efficient data solutions across on‑prem and cloud