Senior Backend Architect: Data Pipelines & AI

Capital One; Richmond (VA); On-site; USD 179,000 - 205,000; Full time

Benefits offered by this job

Health benefits

Performance incentives

Job summary

Capital One seeks a Lead Software Engineer, Back End to architect and scale core data infrastructure in Enterprise Platforms Technology. You will design robust data pipelines, build scalable microservices with Java, Spark, Scala and Spring Boot, and drive AI-enabled development across teams.

You will mentor engineers, optimize cloud-based data workloads on AWS (EMR, Glue, Kinesis), and ensure high availability and data integrity in a fast-paced setting.

Qualifications

• Bachelor’s Degree required.
• 4+ years of professional software engineering experience.
• At least 1 year of cloud computing experience (AWS, Azure, Google Cloud).
• Experience with Java, Scala, Python, or Go is preferred.

Responsibilities

• Architect & Build: lead projects, design scalable data pipelines and microservices using Java, Spark, Scala and Spring Boot.
• Scale for billions: ingest, process, and serve billions of data points with low latency and high availability.
• AI-Enhanced Development: integrate AI coding assistants and autonomous agents into development workflows, testing, and refactoring.
• AI & LLM Integration: design back-end architectures and APIs for AI/ML models and LLM endpoints.
• Technical Leadership: mentor a team of back-end and data engineers, set coding best practices and code reviews.
• Cloud & Data Optimization: leverage AWS services to build cost-effective cloud architectures and tune Spark jobs.
• System Reliability: implement monitoring and automated pipelines for data quality and zero-downtime deployments.

Skills

Java

Apache Spark

Scala

Spring Boot

AWS

Data pipelines

SQL

Education

Bachelor’s Degree

Tools

EMR

Glue

Kinesis

Job description

Capital One seeks a Lead Software Engineer, Back End to architect and scale core data infrastructure in Enterprise Platforms Technology. You will design robust data pipelines, build scalable microservices with Java, Spark, Scala and Spring Boot, and drive AI-enabled development across teams.

You will mentor engineers, optimize cloud-based data workloads on AWS (EMR, Glue, Kinesis), and ensure high availability and data integrity in a fast-paced setting.