Sparkrock
Social benefit organizations
AI-NativeSoftwareEngineeringDirector
Neural analysis suggests this role is
optimal for Director candidates.
“AI-Native Software Engineering Director at Sparkrock. Skills: AI-Native Engineering, Software development, Quality engineering, Experimentation. Design AI-Native Engineering Operating System. Run experiments across software development”
What You'll Achieve.
Create meaningful advantage in speed; Create meaningful advantage in quality; Create meaningful advantage in innovation; Create meaningful advantage in talent leverage; Achieve measurably better outcomes through AI-Native ways of working; Unlock materially higher levels of productivity; Unlock materially higher levels of quality; Unlock materially higher levels of innovation; Improve productivity; Improve quality; Improve speed; Improve developer experience; Improve release confidence; Improve test automation; Improve regression prevention; Improve validation; Improve code review; Improve quality gates; Improve production readiness; Improve engineering productivity; Improve quality; Improve cycle time; Improve developer experience; Improve adoption; Improve business impact; Drive organization-wide adoption; Continuously improve processes
Industry & Context.
Identify engineering bottlenecks; Analyze experiment results; Separate durable engineering value from short-lived AI hype
What They're Looking For.
Must Have
Bachelor's degree or higher in Computer Science, Computer Engineering, Software Engineering, or related field, or equivalent practical experience, 8+ years of hands-on software engineering experience, Strong hands-on software engineering background, Practical experience using AI-assisted development tools, Experience evaluating and rolling out AI engineering tools, Experience leading engineering transformation, Experience designing, executing, measuring, and scaling experiments, Experience improving engineering outcomes through process innovation
Nice to Have
Experience building or scaling AI-Native engineering practices across multiple teams, Experience implementing engineering metrics, Experience defining responsible AI usage standards, Experience with large-scale distributed, remote, or global engineering organizations, Experience with enterprise SaaS, Experience modernizing legacy systems
What You'll Do.
Design AI-Native Engineering Operating System
Run experiments across software development
Run experiments across quality engineering
Evaluate emerging AI engineering tools
Evaluate agentic workflows
Establish AI-Native development standards
Establish AI-Native QA standards
Coach engineers on AI-Native practices
Coach engineering leaders on AI-Native practices
Design and measure AI-Native software development experiments
Design and measure AI-Native quality engineering experiments
Identify engineering bottlenecks for AI-Native workflows
Improve productivity with AI-Native workflows
Improve quality with AI-Native workflows
Improve speed with AI-Native workflows
Improve developer experience with AI-Native workflows
Improve release confidence with AI-Native workflows
Evaluate AI engineering tools
Evaluate coding agents
Evaluate AI-enabled development environments
Evaluate test generation tools
Evaluate code review assistants
Evaluate documentation tools
Evaluate developer productivity platforms
Develop AI-Native development practices
Develop AI-Native testing practices
Develop AI-Native review practices
Develop AI-Native documentation practices
Develop AI-Native refactoring practices
Develop AI-Native debugging practices
Develop AI-Native delivery practices
Define engineering quality bars
Define operating standards
Define usage guardrails
Define workflow templates
Define best practices for AI-assisted software development
Create AI-Native quality engineering practices
Improve test automation
Improve regression prevention
Improve quality gates
Improve production readiness
Establish balanced metrics
Establish measurement frameworks for engineering productivity
Establish measurement frameworks for quality
Establish measurement frameworks for cycle time
Establish measurement frameworks for developer experience
Establish measurement frameworks for adoption
Establish measurement frameworks for business impact
Analyze experiment results
Recommend practices for adoption
Recommend practices for modification
Recommend practices for scaling
Recommend practices for retirement
Create operating models
Create enablement materials
Coach engineers on AI-assisted development
Coach engineers on agentic workflows
Coach engineers on quality engineering
Coach engineers on human-AI collaboration
Coach engineering leaders on AI-assisted development
Coach engineering leaders on agentic workflows
Coach engineering leaders on quality engineering
Coach engineering leaders on human-AI collaboration
Drive organization-wide adoption of AI-Native engineering practices
Define safe practices for AI-generated code
Define responsible practices for AI-generated code
Define safe practices for AI-assisted testing
Define responsible practices for AI-assisted testing
Define safe practices for tool usage
Define responsible practices for tool usage
Define safe practices for data exposure
Define responsible practices for data exposure
Define safe practices for IP protection
Define responsible practices for IP protection
Define safe practices for security
Define responsible practices for security
Define safe practices for maintainability
Define responsible practices for maintainability
Define safe practices for human review
Define responsible practices for human review
Partner with engineering leadership
Partner with product leadership
Partner with QA leadership
Partner with security leadership
Partner with DevOps leadership
Partner with platform leadership
Partner with executive leadership
Align AI-Native transformation efforts with business priorities
Continuously improve software development processes
Continuously improve QA processes
Continuously improve automation processes
Continuously improve CI/CD processes
Continuously improve DevOps processes
Continuously improve cloud engineering processes
Continuously improve observability processes
Continuously improve security processes
Continuously improve delivery processes through AI-Native approaches
Develop strategic recommendations for software engineering evolution
How You'll Work.
Team & Collaboration
Engineering teams; Quality engineering teams; Cross-functional teams; Engineering leaders; Product leadership; QA leadership; Security leadership; DevOps leadership; Platform leadership; Executive leadership
Process & Methodology
Roadmap execution, Release management, Experimentation, Process improvement
Full Job Description
## Description Software engineering is undergoing its biggest transformation since Agile, Cloud, and DevOps. 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 y
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