Software Engineer I

As part of Cox Automotive's Advertising & Marketing Release Train, our engineering teams build the products and platforms that help automotive dealers and OEMs plan, execute, and optimize their advertising — from intelligent budget recommendations and automated campaign management to video production pipelines, third-party ad integrations, and marketing analytics.

We operate within a SAFe Agile framework and deliver value through well-defined Value Streams that connect engineering capabilities to measurable business outcomes.

We are looking for a Software Engineer I who is eager to learn, grow, and contribute to a high-impact team from day one. This is an early-career role designed for engineers who bring foundational technical skills, intellectual curiosity, and a genuine enthusiasm for modern software development practices — including the responsible use of AI-assisted development tools.

In this role, you will work alongside experienced engineers to understand business requirements, develop your technical craft, and contribute to building scalable, resilient, and well-tested systems.

You will begin learning how to leverage AI tools such as GitHub Copilot, Claude Code, and MCP-based workflows to support coding, testing, and documentation tasks — under the guidance of senior team members and with a focus on validating and taking ownership of all AI-generated output.

Our Team

Cox Automotive's Advertising & Marketing teams are spread across Atlanta, GA, Austin, TX, and Burlington, VT. Our release train is home to multiple product engineering teams working across a broad surface area — full-stack web applications, serverless APIs, data pipelines, AI-driven recommendation systems, and advertising automation services — all running on modern cloud infrastructure

Across our teams, we value engineering craft, continuous improvement, and spec-driven development as a growing practice for building well-defined, testable systems. If you are excited to grow your skills in a real-world production environment where collaboration, intentional design, and responsible AI adoption are all part of how we work — you will fit right in

Primary Duties & Key Responsibilities

• Contribute to full-stack feature development across frontend UIs and backend APIs and services, writing clean, readable, and well-tested code under the guidance of senior engineers
• Write unit and integration tests, participate in pair programming, and use AI tools to support code generation, documentation, and troubleshooting — always reviewing output for accuracy, security, and alignment with engineering standards.
• Work within your team to understand and break down epics, features, and stories, building familiarity with how requirements are shaped using AI for problem and solution discovery.
• Learn and apply spec-driven development (SDD) practices by participating in specification reviews and contributing to well-structured specs before implementation begins.
• Develop foundational skills across your team's core technology stack, applying object-oriented design principles to write modular, maintainable, and extensible code.
• Build familiarity with cloud services and begin learning infrastructure-as-code concepts under the guidance of senior engineers.
• Gain exposure to relational and non-relational data stores as part of contributing to data-driven services.
• Learn to troubleshoot issues using traditional debugging techniques and, progressively, AI-assisted root-cause exploration — including supporting production systems through monitoring, alerting, and incident response alongside senior engineers.
• Support platform modernization efforts by assisting with legacy code updates and migration tasks, using AI tools to understand older patterns and propose alternatives.
• Learn and apply secure coding practices and participate in AI-assisted code analysis to identify vulnerabilities or quality concerns.
• Document processes, patterns, and best practices, leveraging AI tools appropriately to produce clear and consistent documentation.
• Share observations and lessons learned from AI-assisted workflows to help refine team practices.
• Communicate status, challenges, and dependencies clearly to teammates, engineering managers, and product stakeholders.

Required Experience, Knowledge & Skills

• Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in the future.
• Bachelor’s degree in Computer Science, Software Engineering, or a related discipline. The right candidate could also have a different combination, such as 4 years' experience in a related field.
• Proficiency in object-oriented programming in at least one modern language (e.g., Java, Python, C#, or similar).
• Good understanding of OOP principles — encapsulation, inheritance, polymorphism — and how they apply to writing clean, maintainable, and extensible code.
• Basic understanding of software development concepts including version control, testing, debugging, and the software development lifecycle.
• Eagerness to learn and grow across a broad technology stack including cloud platforms, data stores, and infrastructure tooling.
• Openness to learning and responsibly adopting AI-assisted development tools (such as, Claude Code, GitHub Copilot and MCP-based workflows) as part of everyday engineering practice.
• Familiarity with or willingness to learn Agile and/or Value Stream-based delivery models.
• Strong communication and teamwork skills with a willingness to take guidance and grow within a collaborative engineering environment.
• Intellectual curiosity, a growth mindset, and a commitment to continuous learning and improvement.

Preferred Qualifications

• Exposure to cloud platforms (AWS, Azure, or GCP).
• Familiarity with web technologies including TypeScript or JavaScript, or experience with a frontend framework such as React or Angular.
• Coursework or project experience with relational or non-relational databases, caching, or distributed systems concepts.
• Basic understanding of CI/CD pipelines, containerization, or infrastructure-as-code concepts.
• Familiarity with testing frameworks or experience writing unit and integration tests.
• Prior internship or professional experience contributing to a production codebase in a team environment.
• Demonstrated ability to learn new technologies quickly through personal projects, open-source contributions, or academic work.