Engineer, Software – Platform Engineering & Applied AI

T-Mobile•Frisco, TX

1d•$92,500 - $166,800•Onsite

About The Position

Build the Next Generation of Enterprise Software Delivery. Modern software engineering is about more than writing code—it's about building resilient platforms, automating repetitive work, improving developer experiences, and applying emerging technologies to solve real business problems. As an Engineer, Software – Platform Engineering & Applied AI, you'll help design, build, and support cloud-native applications and platform services that power critical enterprise capabilities. Working alongside software engineers, architects, platform engineers, and site reliability engineers, you'll contribute to modernizing applications, improving engineering automation, and delivering secure, scalable software solutions. You'll also have the opportunity to explore practical applications of AI-assisted software development, helping improve how software is designed, built, tested, documented, and operated. This team is building the future of enterprise platform engineering. Rather than focusing solely on feature delivery, the team partners across architecture, software engineering, and operations to modernize cloud platforms, improve developer productivity, automate engineering workflows, and simplify complex operational processes. You'll contribute to meaningful technical initiatives while working with experienced architects and engineers who value curiosity, continuous learning, collaboration, and practical problem solving. Engineers are encouraged to explore new technologies, prototype ideas, and help shape modern engineering practices that improve software delivery across the organization.

Requirements

Bachelor's Degree plus 3 years of related work experience OR advanced degree with 1 year of related work experience OR combination of education and experience deemed equivalent (Required)
Acceptable areas of study include Computer Science or Engineering (Required)
2-4 years Technical engineering experience. (Required)
Analytical Thinking
Collaboration
Continuous Development
DevOps
Emerging Technologies
Programming Languages
Software Design
Software Development
Technology Development
Test Evaluation
At least 18 years of age
Legally authorized to work in the United States

Nice To Haves

Experience with one or more of the following technologies or practices is preferred:
Software Development
Java
Spring Boot
RESTful API development
OpenAPI
GraphQL
JavaScript, TypeScript, React, or Angular
Python for automation or tooling
Cloud & Platform Technologies
AWS
Docker
Kubernetes
GitLab CI/CD or similar CI/CD platforms
Microservices architectures
Distributed systems
Data & Integration
Kafka
SQL databases
Snowflake
Databricks
Spark
Security & DevSecOps
Secure software development practices
OAuth2 or Spring Security
Automated testing frameworks
Observability and monitoring platforms
CI/CD automation
Applied AI
AI-assisted software development tools
Prompt engineering
Context engineering
Model Context Protocol (MCP)
Agentic workflow concepts
Internal engineering automation
AI-enabled software development practices
Knowledge of or experience with:
Cloud-native application development
Platform engineering principles
API lifecycle management
Event-driven architectures
Engineering automation
DevSecOps practices
Modern software delivery practices
Distributed systems
Continuous integration and delivery
AI-assisted software engineering
Technical documentation
Cross-functional collaboration
Analytical problem solving
Continuous learning and adaptability

Responsibilities

Develop, test, deploy, and support cloud-native software applications and services.
Build secure, scalable APIs and integrations using modern software engineering practices.
Participate throughout the software development lifecycle, including design, implementation, testing, deployment, monitoring, and operational support.
Troubleshoot production issues and collaborate with cross-functional teams to resolve technical challenges.
Contribute to improving software quality through automated testing, code reviews, documentation, and continuous integration practices.
Contribute to modernization efforts that improve platform scalability, maintainability, and operational efficiency.
Help build internal tools and automation that reduce manual effort and improve engineering productivity.
Partner with architects and engineering teams to evaluate technical approaches and support proof-of-concept initiatives.
Apply secure software development practices throughout the software lifecycle.
Support automation initiatives that improve deployment, testing, monitoring, and operational workflows.
Participate in vulnerability remediation and continuous improvement of software delivery processes.
Utilize AI-assisted development tools to improve software development workflows.
Contribute to engineering automation using emerging AI capabilities where appropriate.
Participate in evaluating practical applications of AI that improve engineering productivity while maintaining appropriate review and governance.
Work collaboratively with software engineers, architects, site reliability engineers, and business partners.
Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives.
Communicate technical concepts clearly with both technical and non-technical stakeholders.