Software Engineer II

Cox Enterprises; Atlanta (GA); Hybrid; USD 100,000 - 150,000; Full time

Job summary

Cox Automotive is seeking a Software Engineer II to apply secure software engineering principles to the design, development, testing, maintenance, and evaluation of software and cloud infrastructure.

This role collaborates with teammates to deliver scalable, resilient systems and to advance enterprise AI initiatives, including building connectors, Python APIs, CI/CD, and IaC while ensuring data safety and compliance.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 2+ years of professional software development experience.
• Proficiency in Python and REST APIs.
• Familiarity with AWS cloud services (Lambda, S3, IAM).
• Experience with version control and code reviews.

Responsibilities

• Build and maintain connectors that integrate Quick with enterprise systems.
• Write clean, tested Python code for APIs and data pipelines.
• Contribute to CI/CD pipelines and infrastructure as code.
• Collaborate with AWS technical teams on secure, scalable solutions.
• Participate in design discussions and contribute to production readiness.

Skills

Python

AWS

APIs

Git

Team collaboration

Education

Bachelor's degree in Computer Science

Tools

Terraform

GitHub Actions

Lambda

S3

IAM

Job description

Cox Automotive is deploying enterprise AI capabilities on AWS Quick across the enterprise, helping teams work more effectively in their day-to-day operations.

The Software Engineer II applies secure software engineering principles to the design, development, testing, maintenance, and evaluation of software and cloud infrastructure. This role collaborates closely with teammates to understand business requirements, contribute to architectural discussions, and deliver scalable, resilient, and secure systems. As part of a corporate-wide AI transformation initiative, this role will also incorporate the responsible use of AI-assisted development tools to streamline coding, testing, troubleshooting, and documentation activities across the SDLC.

This is early-stage work with executive sponsorship, direct access to AWS technical teams, and the chance to grow your skills rapidly in AI platform engineering.

What You'll Do

Build & Ship

• Build and maintain connectors that integrate Quick with enterprise systems — wrapping APIs, handling auth, managing errors, and making data available to AI agents.
• Ship features on the AI Artifact Hub — bug fixes, performance improvements, and new capabilities that make the product better for internal users.
• Write clean, tested Python code for APIs, data pipelines, agent skills, and platform tooling.
• Help enforce integration standards and support domain teams as they publish MCP servers to the enterprise connector catalog.
• Implement features end-to-end: design, code, test, deploy, and monitor in production.

Learn & Grow

• Work closely with senior engineers to learn architecture patterns, code review practices, and production engineering standards.
• Develop expertise in AI platform concepts: RAG, knowledge ingestion, embeddings, agent orchestration, evaluation frameworks, and access control for AI systems.
• Grow your AWS skills through hands-on work with Lambda, S3, IAM, API Gateway, Step Functions, and infrastructure as code.
• Contribute to access control and data safety — help ensure AI agents respect user permissions and never surface unauthorized data in prompt contexts.
• Participate in design discussions — your perspective matters on a small team.

Operate & Support

• Instrument the systems you build — metrics, logging, alerting, and dashboards so the team knows when something is wrong before users do.
• Contribute to evaluation and feedback systems — help build automated test suites that measure agent quality and capture human-in-the-loop corrections.
• Write and maintain CI/CD pipelines (GitHub Actions) and infrastructure as code (Terraform) with guidance from senior team members.
• Contribute to documentation for systems, runbooks, and onboarding materials.
• Participate in on-call rotation with mentorship and support from senior engineers.

Who You Are

• Bachelor’s degree in Computer Science and 2 years’ experience in a related field. The right candidate could also have a
  master’s degree and up to 2 years’ experience; or 14 years’ experience in a related field.
• 2+ years of professional software development experience building production applications or services.
• Proficiency in Python, including writing APIs, scripts, or data processing logic.
• Familiarity with AWS cloud services (e.g., Lambda, S3, IAM, API Gateway) or another major cloud provider.
• Experience with version control (Git) and collaborative development workflows (pull requests, code review).
• Basic understanding of APIs (REST, authentication patterns) and experience integrating with third-party services.
• Eagerness to learn new technologies and grow into more complex engineering challenges.
• Strong communication skills and a collaborative, team-first mindset.
• Applicants must be authorized to work in the United States for any employer without current or future sponsorship.
• Ability to work in the office three days per week.
• Willingness to participate in an on-call rotation with mentorship from senior engineers.

Preferred Qualifications

• Exposure to AI/ML-powered tools, AI APIs, prompt engineering, or building AI-enabled features.
• Experience with Infrastructure as Code (Terraform) or CI/CD pipelines (GitHub Actions).
• Familiarity with the Model Context Protocol (MCP) or building tool/plugin interfaces for AI systems.
• Familiarity with data platforms (Snowflake, Databricks, data lakes, or similar).
• Exposure to authorization models in multi-user systems (row-level security, role-based access).
• Familiarity with cost optimization or FinOps concepts in cloud environments.
• Interest in or exposure to knowledge graphs, embeddings, vector databases, or search systems.
• Experience with event-driven architectures or serverless computing patterns.
• Experience building internal tools, developer platforms, or internal-facing products.
• Prior work in automotive, media, or another large enterprise environment is a plus but not required.