AI-Native Software Engineering Director
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Key skills for this role
About the Role
Jobgether is seeking an AI-Native Software Engineering Director to lead the transformation of software engineering practices by embedding AI-native principles. This fully remote role involves designing experiments, evaluating AI tools, and creating scalable frameworks.
Key Skills for This Role
Responsibilities
- Design, execute, and evaluate AI native engineering experiments across development, testing, and delivery workflows
- Identify and address engineering bottlenecks using AI assisted tools, workflows, and automation strategies
- Evaluate and implement emerging AI development tools, coding agents, and productivity platforms
- Define and institutionalize AI native engineering standards, practices, guardrails, and quality frameworks
- Develop AI enabled quality engineering approaches to improve testing, validation, code review, and production readiness
- Establish metrics and measurement systems to assess productivity, quality, developer experience, and delivery performance
- Analyze experimental outcomes and determine scalability, refinement, or retirement of practices
- Create playbooks, frameworks, and enablement materials to standardize successful AI native practices
- Coach and support engineers and technical leaders in adopting AI driven workflows and practices
- Drive organization wide adoption of AI native engineering through influence, training, and continuous improvement loops
- Define responsible AI usage policies for code generation, security, compliance, and maintainability
- Partner with cross functional and executive stakeholders to align AI transformation with business objectives
Requirements
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 8+ years of hands on software engineering experience building production grade systems
- Strong background in modern software engineering practices, including CI/CD, DevOps, testing, and cloud native development
- Experience using AI assisted development tools, coding agents, or AI powered engineering workflows in real production environments
- Proven experience driving engineering transformation, developer productivity, or technical enablement initiatives
- Experience designing and scaling experiments to improve engineering outcomes and organizational performance
- Strong ability to define engineering metrics, interpret results, and drive data informed decisions
- Experience establishing engineering standards, quality frameworks, and operational best practices
- Excellent coaching, mentoring, and change leadership skills across technical teams
- Strong systems thinking with the ability to optimize complex engineering and organizational workflows
- Ability to clearly communicate technical and strategic concepts to diverse audiences, including executives
- Experience distinguishing durable engineering improvements from short term technology trends
Full Job Posting
Job Overview
- In this role, you will lead the transformation of software engineering practices by embedding AI native principles into how modern engineering teams design, build, test, and deliver software.
- You will focus on defining and operationalizing a new engineering model powered by AI assisted development, agentic workflows, and data driven experimentation.
- This is a strategic, high impact role for a leader passionate about redefining the future of software engineering.
Accountabilities
- Design, execute, and evaluate AI native engineering experiments across development, testing, and delivery workflows
- Identify and address engineering bottlenecks using AI assisted tools, workflows, and automation strategies
- Evaluate and implement emerging AI development tools, coding agents, and productivity platforms
- Define and institutionalize AI native engineering standards, practices, guardrails, and quality frameworks
- Develop AI enabled quality engineering approaches to improve testing, validation, code review, and production readiness
- Establish metrics and measurement systems to assess productivity, quality, developer experience, and delivery performance
- Analyze experimental outcomes and determine scalability, refinement, or retirement of practices
- Create playbooks, frameworks, and enablement materials to standardize successful AI native practices
- Coach and support engineers and technical leaders in adopting AI driven workflows and practices
- Drive organization wide adoption of AI native engineering through influence, training, and continuous improvement loops
- Define responsible AI usage policies for code generation, security, compliance, and maintainability
- Partner with cross functional and executive stakeholders to align AI transformation with business objectives
Requirements
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 8+ years of hands on software engineering experience building production grade systems
- Strong background in modern software engineering practices, including CI/CD, DevOps, testing, and cloud native development
- Experience using AI assisted development tools, coding agents, or AI powered engineering workflows in real production environments
- Proven experience driving engineering transformation, developer productivity, or technical enablement initiatives
- Experience designing and scaling experiments to improve engineering outcomes and organizational performance
- Strong ability to define engineering metrics, interpret results, and drive data informed decisions
- Experience establishing engineering standards, quality frameworks, and operational best practices
- Excellent coaching, mentoring, and change leadership skills across technical teams
- Strong systems thinking with the ability to optimize complex engineering and organizational workflows
- Ability to clearly communicate technical and strategic concepts to diverse audiences, including executives
- Experience distinguishing durable engineering improvements from short term technology trends
Benefits
- Fully remote global work environment with flexible working hours and asynchronous collaboration
- Opportunity to define AI native engineering practices at organizational scale
- Access to cutting edge AI engineering tools and platforms for experimentation and innovation
- Strong focus on professional growth, continuous learning, and career development support
- Home office setup stipend to support remote productivity
- Collaborative culture including virtual events, knowledge sharing sessions, and community activities
- Exposure to thought leaders and cutting edge discussions in AI and software engineering
- Inclusive, diverse, and mission driven work environment
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