Lead Back-End Engineer — AI‑Driven Messaging Platform

Capital One; McLean (VA); On-site; USD 197,300 - 225,100; Full time

Job summary

Capital One is seeking a Lead Back End Software Engineer who is passionate about Artificial Intelligence, Machine Learning, and building intelligent solutions with emerging technologies. You will lead a team of developers, guide architecture decisions, and deliver cloud-based microservices using Java, Python, and Go.

You will collaborate with product managers to create robust, personalized experiences at scale, leveraging AWS ecosystems and modern tooling to drive performance and data-driven

Qualifications

• Bachelor’s degree in a technical field.
• 4+ years of professional software engineering experience.
• At least 1 year of cloud computing experience (AWS, Azure, GCP).
• Preferred: Master’s degree and 7+ years in multiple languages.
• Experience with open source frameworks and large-scale projects.
• Experience with Agile practices and big data ETL tools.
• Experience with Generative AI coding tools and LLM capabilities.

Responsibilities

• Lead a portfolio of diverse technology projects with a team of developers.
• Collaborate with product managers to design robust cloud-based solutions.
• Direct design, development, testing, and implementation using AI technologies and LLMs in the cloud.
• Leverage Java, JavaScript, Python, and Go in a modern AWS-based stack.
• Mentor engineers and uphold high standards through code reviews.

Skills

Java

JavaScript

Python

Go

TypeScript

SQL

Cloud computing

leadership

AI

LLMs

Education

Bachelor's Degree

Master's Degree

Tools

AWS

GCP

Azure

Databricks

Dataflow

AWS Glue

Job description

Capital One is seeking a Lead Back End Software Engineer who is passionate about Artificial Intelligence, Machine Learning, and building intelligent solutions with emerging technologies. You will lead a team of developers, guide architecture decisions, and deliver cloud-based microservices using Java, Python, and Go.

You will collaborate with product managers to create robust, personalized experiences at scale, leveraging AWS ecosystems and modern tooling to drive performance and data-driven