Senior AI-Native Software Engineer

AT&T•Dallas, TX

1d•$143,800 - $215,800•Onsite

About The Position

This is a full-time onsite role based in the location(s) posted and is performed from the designated work location five days per week. No relocation is offered. Join our Billing Engineering team and help redefine how enterprise software is built. We're looking for a highly skilled software engineer who combines deep backend engineering expertise with a passion for AI-assisted development. In this role, you'll design and deliver modern digital platforms while pioneering the use of Generative AI, LLMs, and agentic engineering tools to dramatically accelerate software delivery, improve code quality, and enhance developer productivity. You'll serve as a force multiplier across the organization by helping teams adopt AI-powered development practices that transform the software development lifecycle.

Requirements

Passion for building modern software while pushing the boundaries of AI-assisted engineering.
Proven ability to leverage AI and automation to improve engineering velocity and developer experience.
Strong problem-solving skills with a focus on scalability, reliability, and maintainability.
A continuous learning mindset and enthusiasm for staying current with emerging AI models, developer tools, and software engineering trends.
Excellent communication and collaboration skills with the ability to mentor engineers and influence technical direction.
Experience balancing rapid innovation with enterprise-grade quality, security, and governance requirements.
5+ years of professional software engineering experience developing and deploying enterprise applications and distributed systems.
Strong proficiency in at least one modern backend technology stack: Java / Spring Boot Python / FastAPI / Django Go Node.js
Hands-on experience building microservices, APIs, and cloud-native applications.
Demonstrated expertise using AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, Devin, or similar technologies within a professional engineering environment.
Experience with testing frameworks such as JUnit, PyTest, Mockito, or equivalent.
Strong knowledge of API architectures including REST, GraphQL, and gRPC.
Experience with PostgreSQL, Oracle, MongoDB, or similar database technologies.
Solid understanding of Git workflows, trunk-based development, CI/CD pipelines, and modern software delivery practices.
Familiarity with event-driven architectures and messaging platforms such as Kafka or JMS.

Nice To Haves

Experience designing enterprise AI coding frameworks, prompt libraries, or custom developer productivity tooling.
Experience modernizing legacy applications and monolithic platforms through AI-assisted refactoring.
Knowledge of Agentic AI workflows and autonomous engineering tools.
Contributions to open-source projects, developer tools, internal platforms, or software productivity initiatives.
Experience building AI-enhanced software development workflows at scale.

Responsibilities

Build and Modernize Enterprise Platforms: Design, develop, and deploy scalable microservices and high-performance APIs using technologies such as Java/Spring Boot, Python, Node.js, or Go.
Develop enterprise-grade digital capabilities including API gateways, event-driven architectures, messaging systems, and cloud-native services.
Build integrations with relational and NoSQL databases while ensuring reliability, security, and scalability.
Deliver production-ready software that follows clean code principles, modern architectural standards, and secure development practices.
Accelerate Engineering Through AI: Leverage AI coding assistants including GitHub Copilot, Cursor, Devin, and other agentic development tools to increase speed, efficiency, and software quality.
Create reusable prompt frameworks, engineering workflows, and automation scripts that eliminate repetitive development tasks.
Utilize Generative AI to automate testing, code generation, documentation, refactoring, and modernization efforts.
Evaluate emerging AI technologies and identify opportunities to improve engineering productivity across teams.
Champion Developer Productivity: Lead adoption of AI-assisted software engineering best practices across development teams.
Coach engineers on prompt engineering, context management, code review techniques, and responsible use of generative AI.
Review both human-generated and AI-generated code to ensure maintainability, security, and compliance with architectural standards.
Partner closely with product, architecture, and platform teams to rapidly prototype and deliver new capabilities.
Drive CI/CD improvements including AI-powered code quality analysis, automated testing, pull request summarization, and deployment automation.

Benefits

Medical/Dental/Vision coverage
401(k) plan
Tuition reimbursement program
Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
Paid Parental Leave
Paid Caregiver Leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
Employee Assistance Programs (EAP)
Extensive employee wellness programs
Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone