Role Overview

At Harness, we are on a mission to enable every software developer to deliver code to their users reliably, efficiently, and securely. As Director of Engineering Quality & Automation, you will own the technical strategy, systems, and culture that ensure Harness ships high-quality software at scale — through rigorous testing infrastructure, release reliability, and AI-native automation. 

You will lead a large team,within a distributed engineering organization of 40–60+ engineers and engineering managers responsible for test automation, quality gates, CI/CD reliability, and intelligent automation across the software delivery lifecycle. You will build a quality-first, automation-driven engineering culture that sets the global benchmark for reliable, AI-assisted software delivery.

This is a high-impact leadership role requiring deep SaaS expertise, strong operational execution, and a passion for quality engineering, test automation, and AI-driven workflows. You will partner closely with product engineering, infrastructure, SRE, and security teams to raise the bar on engineering quality and automate away manual toil.

Key Responsibilities

1. Quality & Automation Strategy

• Define and execute the vision and roadmap for engineering quality, test automation, and release reliability.
• Establish scalable foundations for CI/CD reliability, testing infrastructure, and automated quality gates.
• Champion AI-native quality practices, integrating generative AI, intelligent automation, and agentic workflows into testing and release processes.
• Partner with product and platform engineering teams to embed quality and automation standards into every stage of the SDLC.

2. Testing Infrastructure & Release Reliability

• Own and optimize testing infrastructure and release engineering, ensuring teams can reliably ship multiple production releases per day without compromising quality.
• Build and evolve scalable, cost-effective, multi-cloud, Kubernetes-based testing infrastructure that eliminates flakiness.
• Standardize automated testing frameworks, quality gates, and deployment validation across microservices and multi-tenant SaaS environments.
• Ensure testing and release systems meet high standards for scalability, resilience, and availability.

3. Quality Metrics & Continuous Improvement

• Establish data-driven quality and reliability metrics using DORA, SPACE, and Software Engineering Insights like frameworks.
• Analyze and eliminate quality bottlenecks across CI/CD pipelines, test systems, and release workflows.
• Drive measurable improvements in change failure rate, MTTR, build reliability, test coverage, and defect escape rate.
• Build executive-level visibility into engineering quality, release health, and automation ROI.

4. AI-Native Automation

• Drive automation initiatives that eliminate repetitive manual work across testing, release validation, and quality operations.
• Pioneer AI-assisted and agentic testing practices where intelligent systems generate test cases, optimize pipelines, detect issues, and assist in remediation.
• Integrate AI-powered tooling into testing systems, quality gates, and release orchestration to improve release confidence.
• Improve reliability engineering through advanced automated testing and intelligent quality gates.

5. Leadership & Talent Management

• Lead, mentor, and grow a globally distributed quality and automation engineering organization.
• Build a high-performance, execution-oriented culture focused on ownership, rigor, and continuous improvement.
• Recruit and retain top quality engineering and automation talent, with strong collaboration across US and India teams.
• Develop leadership pipelines and clear career growth frameworks for quality and automation engineers.

Core Focus Areas

1. Engineering Quality
   • High availability and reliability engineering
   • Scalable testing infrastructure and automation
   • CI/CD excellence and release reliability
   • Operational maturity and engineering governance
2. Developer Experience
   
   • Reducing developer friction and toil
   • Improving onboarding and engineering workflows
   • Accelerating feedback loops and development cycles
   • Building intuitive, self-service developer platforms
3. Infrastructure Excellence
   • Cost effective Cloud-native and Kubernetes-based engineering systems for reliable testing
   • Scalable multi-cloud SaaS testing infrastructure to remove flakiness
   • Internal developer platform engineering and developer enablement
   • AI-native productivity and automation systems

Minimum Qualifications

Experience

• 12+ years of software engineering experience with substantial leadership experience managing large-scale engineering organizations.
• 5+ years in senior engineering leadership roles (Director or above) focused on Quality Engineering, Test Automation, CI/CD, or Release Engineering.
• Proven experience leading distributed teams of 10–20+ engineers and managers.

Technical Expertise

• Strong background in software engineering, cloud-native architecture, CI/CD systems, distributed systems, and large-scale test infrastructure.
• Deep real-world experience operating Continuous Deployment and Continuous Delivery at scale.
• Strong understanding of Kubernetes, microservices architecture, and test automation frameworks.
• Practical experience with AI-powered quality systems, intelligent test automation, or agentic workflows is highly preferred.

Leadership

• Demonstrated success leading engineering managers and technical leads in fast-paced, high-growth SaaS environments.
• Strong operational leadership, execution discipline, and cross-functional collaboration skills.
• Experience building high-performance remote and hybrid engineering organizations across global geographies.

Education

• Bachelor's degree in Computer Science, Engineering, or equivalent.

Preferred Qualifications

• Experience building enterprise-scale test automation or quality engineering organizations.
• Growth mindset with drive to take initiatives 
• Familiarity with DORA metrics, SPACE framework, and Software Engineering Intelligence systems.
• Experience with enterprise-grade SaaS reliability and release management practices.
• Prior experience scaling quality and automation systems in hyper-growth environments.