AI-Native Software Engineering Director Sparkrock

Software engineering is undergoing its biggest transformation since Agile, Cloud, and Dev Ops. AI is changing how software is designed, built, tested, reviewed, documented, and delivered. The organizations that learn how to turn this shift into disciplined engineering practice will create a meaningful advantage in speed, quality, innovation, and talent leverage.

At Sparkrock, we help social benefit organizations—such as nonprofits, school boards, and government agencies—operate more effectively. Every day, tens of thousands of users rely on our platforms to manage critical financial and administrative workflows.

Sparkrock is looking for an AI-Native Software Engineering Director to lead that transformation. This is not a traditional software engineering leadership role focused on roadmap execution, release management, or managing a large reporting line. Your mission is to build the AI-Native Engineering Operating System for Sparkrock: the experiments, workflows, standards, metrics, guardrails, playbooks, and coaching systems that define how our engineering teams build software in the AI era.

You will design and run experiments across software development and quality engineering, evaluate emerging AI engineering tools and agentic workflows, establish AI-Native development and QA standards, and coach engineers and engineering leaders to unlock materially higher levels of productivity, quality, and innovation.

This role offers a unique opportunity to shape the future of software engineering within a global, fully remote organization. You will directly influence how engineering teams use AI-assisted development, coding agents, quality automation, and human-AI collaboration to build exceptional software safely, reliably, and at scale.

Success in this role is measured by your ability to help engineering teams achieve measurably better outcomes through AI-Native ways of working, not by the size of the team you manage or the number of tools you introduce.

If you are passionate about the future of engineering, energized by experimentation, serious about quality, and motivated by helping engineers achieve breakthrough performance through AI-Native practices, we would love to hear from you.

• Design, execute, and measure AI-Native software development and quality engineering experiments.
• Identify engineering bottlenecks where AI-Native workflows can improve productivity, quality, speed, developer experience, or release confidence.
• Evaluate emerging AI engineering tools, coding agents, AI-enabled development environments, test generation tools, code review assistants, documentation tools, and developer productivity platforms.
• Develop and institutionalize AI-Native development, testing, review, documentation, refactoring, debugging, and delivery practices.
• Define and maintain engineering quality bars, operating standards, usage guardrails, workflow templates, and best practices for AI-assisted software development.
• Create AI-Native quality engineering practices that improve test automation, regression prevention, validation, code review, quality gates, and production readiness.
• Establish balanced metrics and measurement frameworks for engineering productivity, quality, cycle time, developer experience, adoption, and business impact.
• Analyze experiment results and recommend whether practices should be adopted, modified, scaled, or retired.
• Create playbooks, frameworks, operating models, and enablement materials that turn successful experiments into repeatable practices across the organization.
• Coach engineers and engineering leaders to maximize effectiveness through AI-assisted development, agentic workflows, quality engineering, and human-AI collaboration.
• Drive organization-wide adoption of proven AI-Native engineering practices through coaching, enablement, influence, measurement, and continuous feedback loops.
• Define safe and responsible practices for AI-generated code, AI-assisted testing, tool usage, data exposure, IP protection, security, maintainability, and human review.
• Partner with engineering, product, QA, security, Dev Ops, platform, and executive leadership to align AI-Native transformation…