Director, AI Assisted Software Engineering
New
J
JobgetherSoftware Engineering
Full-time remote work from any location within the United States.Full-TimeDirector
Salary170,144 - 230,000 USD per year
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Job Details
- Experience
- 5+ years of progressive software engineering experience with 3–5+ years in technical leadership; 10+ years of software engineering experience is preferred.
- Required Skills
- PythonFull Stack DevelopmentJavaJavascriptSoftware ArchitectureCI/CDLLM
Requirements
- Bachelor’s degree in Computer Science, Engineering, or related discipline, or equivalent professional experience.
- 5+ years of progressive software engineering experience with 3–5+ years in technical leadership.
- Strong understanding of AI-assisted development workflows including prompt engineering, code-generation loops, and safety validation.
- Direct experience selecting and operationalizing AI development tools like GitHub Copilot, Azure AI, or Claude Code.
- Hands-on experience with LLM-based frameworks and RAG in software delivery environments.
- Proven ability to establish adoption roadmaps, capability models, and organizational change initiatives.
- Strong technical leadership defining architecture standards across multi-team programs.
- Knowledge of CI/CD, DevSecOps, TDD/BDD, automation, and quality engineering practices.
- Full-stack development proficiency with languages such as Java, JavaScript, Python, and .NET.
- Experience with frameworks like Angular, React, Spring Boot, Django, or Next.js.
- Experience developing in Linux/Unix environments (e.g., RHEL, OpenShift).
- Excellent communication and stakeholder management skills.
Responsibilities
- Define strategy, operating models, and best practices for enterprise-wide AI-assisted software development.
- Evaluate and operationalize AI-enabled development tools and establish responsible adoption practices.
- Lead and scale engineering teams through hiring, coaching, mentoring, and capability development.
- Develop developer education programs, playbooks, and communities of practice to support organization-wide transformation.
- Drive technical vision and architecture standards across complex, multi-team software programs.
- Establish and improve engineering practices including CI/CD, DevSecOps, TDD/BDD, and quality engineering.
- Track and communicate business value and ROI for AI adoption and productivity improvements.
- Collaborate with senior stakeholders to influence organizational decisions and support emerging technology adoption.
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