Director of Quality Engineering & Automation

Harness is the AI Software Delivery Platform company led by technologist and entrepreneur Jyoti Bansal (founder of AppDynamics acquired by Cisco for $3.7B). Harness has raised approximately $570M in funding and is valued at $5.5B backed by leading investors including Goldman Sachs Menlo Ventures IVP Unusual Ventures Citi Ventures and more. As AI accelerates code creation the real bottleneck has shifted to everything after the code testing deployments application security reliability compliance and cost optimization. Harness brings AI and automation to this outer loop helping teams ship software faster while maintaining security and governance throughout the entire software delivery lifecycle.

Powered by Harness AI and the Software Delivery Knowledge Graph the Harness Platform applies deep context and intelligent automation across the software delivery lifecycle with governance and policy-driven controls embedded throughout the platform.

Over the past year Harness powered over 185M deployments 82M builds 18T flag evaluations 8M security scans 9.1B optimized tests 3T protected API calls and helped manage $2.8B in cloud spend enabling customers like United Airlines Morningstar and Choice Hotels to accelerate releases by up to 75% reduce cloud costs by up to 60% and achieve 10x DevOps efficiency.

With a global team across 26 offices and 27 countries Harness is shaping the future of AI software delivery and were looking for exceptional talent to help us move even faster.

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 teamwithin a distributed engineering organization of 4060 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 andrelease reliability.
• Establish scalable foundations for CI/CD reliability testing infrastructure and automatedquality gates.
• Champion AI-native quality practices integrating generative AI intelligent automationand agentic workflows into testing and release processes.
• Partner with product and platform engineering teams to embed quality and automationstandards into every stage of the SDLC.

2. Testing Infrastructure & Release Reliability

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

3. Quality Metrics & Continuous Improvement

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

4. AI-Native Automation

• Drive automation initiatives that eliminate repetitive manual work across testing releasevalidation and quality operations.
• Pioneer AI-assisted and agentic testing practices where intelligent systems generate testcases optimize pipelines detect issues and assist in remediation.
• Integrate AI-powered tooling into testing systems quality gates and releaseorchestration to improve release confidence.
• Improve reliability engineering through advanced automated testing and intelligentquality 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 1020 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

• Bachelors 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.

Harness in the news:

• Accelerating Our Mission to Bring AI to Everything After Code
• Goldman Sachs leads investment in software delivery startup Harness at $5.5 billion valuation
• How Harness runs 16 startups within a startup at scale Jyoti Bansal
• Harness Research Shows AI Visibility Crisis Fueling Security Nightmare
• Harness has been named to the Inc. Power Partner list for software delivery success

All qualified applicants will receive consideration for employment without regard to race color religion sex or national origin.

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