AI-Native Software Engineering Director

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

• 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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