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Atlanta, Georgia, United States
Remote only
The AI Software Engineer is responsible for helping establish, scale, and operationalize AI-assisted software development practices within the Engineering organization. This role will demonstrate how high-quality, revenue-impacting software can be delivered through an autonomous development model where AI agents generate code, engineers validate outcomes through testing and review, and teams continuously improve delivery velocity without sacrificing quality, security, or compliance.
This role will drive the adoption of repeatable AI-enabled engineering workflows, deliver strategic product enhancements, develop standards and playbooks, and coach engineers to independently execute autonomous development practices across multiple teams. As the organization’s AI-enabled development capabilities mature, this position is expected to evolve into a broader technical leadership role focused on engineering enablement, adoption, and organizational capability building.
Lead the implementation of AI-assisted software development practices across engineering teams.
Deliver revenue-impacting software enhancements using autonomous development and human review workflow.
Establish and continuously improve standards, governance processes, and quality controls for AI-generated code.
Create and maintain engineering playbooks, best practices, and operating procedures for autonomous software delivery.
Partner closely with Engineering, Product, Architecture, and Applied AI teams to align priorities and remove delivery obstacles.
Develop automated build, testing, and validation frameworks that enable rapid and reliable code verification.
Ensure delivered solutions meet established quality, security, compliance, and testing requirements.
Coach and mentor engineers on effectively leveraging AI tools throughout the software development lifecycle.
Develop and deliver training, workshops, and enablement resources that build organizational capability in AI-assisted software development.
Monitor adoption, measure effectiveness, and continuously improve AI-enabled engineering practices.
Contribute to communities of practice that promote knowledge sharing and continuous improvement across engineering teams.
Serve as a champion for modern software engineering practices, automation, and AI-enabled productivity.
Take on increasing technical leadership responsibilities over time, with the opportunity to grow into a formal leadership role as AI-assisted development practices scale across the organization.
Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent experience.
5+ years leading software development initiatives in complex enterprise environments.
Strong background in software engineering, application architecture, and modern development practices.
Experience working with AI-assisted coding tools, developer productivity platforms, or software automation technologies.
Demonstrated success delivering software products through Agile methodologies.
Deep understanding of software testing, quality assurance, CI/CD pipelines, and release management.
Experience mentoring engineers and driving organizational adoption of new technologies and workflows.
Ability to balance innovation, speed, quality, and risk management.
Strong collaboration and communication skills with both technical and non-technical stakeholders.
Experience creating technical standards, governance models, playbooks, or enablement programs.
Proven ability to manage multiple priorities and drive measurable business outcomes.
Familiarity with compliance, security, and regulated software development environments.
Experience implementing AI-first or autonomous software development practices at scale.
Proven track record of improving engineering productivity through automation and intelligent tooling.
Experience leading organizational change and technology transformation initiatives.
Strong understanding of human-in-the-loop development models and AI governance frameworks.
Ability to create repeatable engineering processes that can be adopted across multiple teams.
Experience coaching engineers to effectively partner with AI tools while maintaining engineering excellence.
Demonstrated success building communities of practice, training programs, or capability-building initiatives.
Background working in highly regulated industries such as healthcare, financial services, or government.
Experience measuring and communicating the business impact of engineering transformation programs.
Passion for exploring emerging AI technologies and translating them into practical engineering outcomes.