Lead Software Engineer - Python

GameStop•Grapevine, TX

4d•Onsite

About The Position

This position helps establish a brand-new platforms team within the engineering organization. You will collaborate closely with engineering leadership and many other engineering teams to build new systems from the ground up. The ideal candidate leads the development of robust, cloud-native back-end solutions and contributes significantly to intuitive, responsive front-end interfaces — while setting the standard for AI-assisted engineering, automated quality, and modern cloud architecture across the team. This position sits onsite in Grapevine, TX 5 days per week.

Requirements

8+ years of software development experience.
4+ years of deep, hands-on experience building and operating production systems on a major cloud platform (AWS, Azure, or GCP) — including containers/Kubernetes, managed services, and cloud-native architecture patterns.
7+ years of experience with Python.
Experience architecting and developing intuitive front-end interfaces using React and Redux.
Hands-on experience with CI/CD and test automation (e.g., pytest, Playwright/Selenium) and infrastructure-as-code.
Working proficiency with AI-assisted development tooling and a clear point of view on using it responsibly in a team setting.
Proven progression from Software Engineer to technical leadership roles, with increasing responsibility and impact.
Demonstrated ownership of major technical projects from conception to delivery.
Demonstrated ability to solve complex technical problems with strong analytical skills and creativity.
Excellent interpersonal and communication skills, including translating technical concepts for non-technical stakeholders.

Nice To Haves

Desire to thrive in a fast-paced environment.
Depth in AWS specifically (the team's primary cloud).
Experience integrating LLM/agentic capabilities or AI/ML services into production products at scale.
Experience defining SRE / operational reliability practices for large-scale distributed systems.

Responsibilities

Architect, design, and build critical back-end systems — such as payments and transaction technologies — as well as intuitive front-end interfaces.
Design and operate cloud-native systems on a major cloud platform (AWS, Azure, or GCP), using Kubernetes, containers, microservices, and service-oriented architecture, with an eye to scalability, resilience, and cost efficiency.
Own non-functional concerns — observability, performance, security, and operational reliability (SRE practices, SLOs) — for the platforms the team builds.
Lead adoption of AI-assisted development and agentic tooling (e.g., GitHub Copilot, Claude Code, LLM-based code review and test generation), modeling best practices for the new platforms team.
Establish quality and security guardrails so AI accelerates delivery without degrading code quality, IP integrity, or compliance.
Evaluate and integrate AI/LLM capabilities into products and developer workflows where they add measurable value.
Drive a shift-left quality strategy — automated unit, integration, and regression testing embedded in CI/CD pipelines.
Set and uphold coverage, reliability, and quality-gate standards, holding the line on quality as AI increases commit velocity.
Be an advocate for engineering best practices across front-end and back-end development, and mentor engineers on the new platforms team.
Operate as a fluent agile practitioner, helping the new team establish healthy delivery cadence and engineering-effectiveness metrics (e.g., DORA: deployment frequency, lead time, change-failure rate, MTTR).