AI-Native Software Engineering Director
New
S
SparkrockEnterprise SaaS
This role is open to applicants from any country. We hire globally.Full-TimeDirector
SalaryBase: $90,000 – $108,000 base. OTE USD: $100,000 – $120,000. Variable: 10%.
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Job Details
- Experience
- 8+ years
- Required Skills
- CI/CDDevOpsSoftware EngineeringChange Management
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
- 8+ years of hands-on software engineering experience delivering production software systems.
- Strong background in modern software development practices and production-grade systems.
- Practical experience using AI-assisted development tools, coding agents, or AI-enabled IDEs in real environments.
- Experience evaluating and rolling out AI engineering tools, coding agents, or developer productivity platforms.
- Experience leading engineering transformation, developer productivity, or quality engineering initiatives.
- Experience designing, executing, and scaling experiments that improve engineering productivity or quality.
- Experience driving the adoption of new engineering practices across multiple teams.
- Experience coaching engineers and leaders through changes in practices or operating models.
- Strong understanding of CI/CD, DevOps, cloud-native development, and software testing strategies.
- Exceptional change leadership, coaching, and analytical communication skills.
Responsibilities
- 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, and developer productivity platforms.
- Develop and institutionalize AI-Native development, testing, review, documentation, and delivery practices.
- Define and maintain engineering quality bars, operating standards, usage guardrails, and best practices.
- Establish balanced metrics and measurement frameworks for engineering productivity and quality.
- Coach engineers and leaders to maximize effectiveness through AI-assisted development and agentic workflows.
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