Associate Software Engineer

Aderant • Atlanta, GA

23h

About The Position

Aderant is a global industry leading software company providing comprehensive business management solutions for law firms and other professional services organizations with a mission to help them run a better business. We are motivated by a collective desire to drive the legal industry to the forefront of innovation. With over 2,500 clients around the world, including 95 of the top AmLaw 100 firms, we are changing the outside perception of the legal sphere; where there was once resistance to modernization, we are creating a culture that embraces new ideas and technology. At Aderant, the “A” is more than just a letter. It is a representation of how we fulfill our foundational purpose, serving our clients. It embodies our core values and reminds us that to achieve success, every day must start with the “A”. We bring the “A” to life by fostering a culture of innovation, collaboration, and personal growth. We encourage our diverse teams to bring their whole selves to work – ideas, experience, and passion – to drive our mission forward. Our people are our strength. We’re hiring a Junior Full Stack Software Engineer to join our team and help build the products our customers rely on every day. This role is designed for recent graduates who are excited about modern software development — and just as excited about using AI tools to write better code, faster. You’ll work across the stack (frontend, backend, and data), pair with senior engineers, and ship real features in your first few months. We treat AI coding assistants (Claude Code, Cursor, GitHub Copilot, and similar tools) as a core part of how we build software. We’re looking for someone who is genuinely curious about getting the most out of these tools — not as a shortcut, but as a force multiplier on top of solid engineering fundamentals.

Requirements

• A bachelor’s degree in Computer Science, Software Engineering, or a related field — or equivalent practical experience (bootcamp, self-taught, strong portfolio).
• Working knowledge of at least one frontend framework (React preferred) and one backend language (TypeScript/Node.js, Python, Go, or Java).
• Familiarity with relational databases, REST or GraphQL APIs, and Git-based workflows.
• Solid fundamentals: data structures, algorithms, HTTP, and how the browser and server actually talk to each other.
• Clear written and verbal communication — you can explain what you built, why, and where you got stuck.
• A bias toward shipping, learning in public, and asking good questions.
• Prompting deliberately — breaking work into well-scoped tasks, providing relevant files and context, and iterating on prompts the way you’d iterate on code.
• Knowing when AI helps and when it doesn’t — reaching for it for boilerplate, refactors, test generation, and exploration; staying hands-on for security-sensitive code, novel architecture, and anything you don’t yet understand.
• Reviewing AI output critically — never merging code you can’t explain, and treating model suggestions as a first draft, not a final answer.
• Using agentic tools responsibly — running them in safe sandboxes, scoping permissions tightly, and verifying changes before they leave your machine.
• Sharing what works — contributing prompts, .cursorrules, CLAUDE.md files, and workflow tips back to the team.

Nice To Haves

• Open-source contributions, side projects, hackathon work, or a GitHub profile you’re proud of.
• Internship or co-op experience as a software engineer.
• Exposure to cloud platforms (AWS, GCP, or Azure) and containerization (Docker).
• Experience building something interesting with LLM APIs, RAG, or agent frameworks — even a weekend project counts.
• Familiarity with CI/CD pipelines, observability tools, or basic infrastructure-as-code.

Responsibilities

• Build and maintain features across the full stack — React/TypeScript on the frontend, Node.js or Golang services on the backend, and SQL/NoSQL data stores.
• Use AI coding assistants daily to scaffold features, draft tests, refactor legacy code, and accelerate debugging — while taking full ownership of the code you ship.
• Write clear technical specs and tickets that give both your teammates and AI tools enough context to do their best work.
• Participate in code reviews — reviewing AI-generated and human-written code with the same critical eye.
• Contribute to internal tooling, prompt libraries, and team playbooks that help everyone use AI more effectively.
• Pair with senior engineers on larger systems work, gradually taking on more design and architectural responsibility.
• Write tests, fix bugs, monitor production, and help on-call rotations once ramped up.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level