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 the Director of Engineering Productivity, and Developer Experience you will drive the technical strategy, tools, and infrastructure that increase engineering velocity, quality, reliability, and efficiency across the company.

You will lead a large, distributed engineering organization of 40–60+ engineers and engineering managers responsible for optimizing development workflows, CI/CD systems, testing infrastructure, release engineering, developer platforms, and AI-native productivity tooling. You will build a "10x" engineering culture that sets the global benchmark for what it means to be AI-native

This is a high-impact leadership role requiring deep SaaS expertise, strong operational execution, and a passion for developer experience, quality engineering, automation, and AI-driven workflows. You will partner closely with product engineering, infrastructure, SRE, security, and executive leadership teams to champion polished, scalable, high-velocity engineering practices across Harness.

Key Responsibilities

1. Strategic Leadership & Technical Roadmap

• Define and execute the vision and roadmap for Engineering Productivity and internal developer platforms.
• Drive the technical strategy, tools, and infrastructure necessary to improve developer velocity, engineering quality, release reliability, and operational excellence.
• Establish scalable foundations for CI/CD, testing, developer environments, observability, release orchestration, and engineering insights.
• Champion AI-native engineering practices, integrating generative AI, intelligent automation, and agentic workflows into the SDLC.
• Partner with product and platform engineering teams to ensure scalable, reliable, and developer-friendly engineering standards.

2. Tooling, Infrastructure & Developer Platforms

• Build and evolve internal platforms, frameworks, and tooling that improve software engineering efficiency and product excellence.
• Own and optimize the internal SDLC, ensuring teams can reliably deliver multiple production releases per day without compromising quality.
• Improve development workflows across microservices, Kubernetes, cloud infrastructure, and multi-tenant SaaS environments.
• Standardize and streamline build systems, developer environments, test infrastructure, deployment pipelines, and release engineering practices.
• Ensure internal platforms meet high standards for scalability, resilience, security, and availability.

3. Engineering Productivity & Metrics

• Establish data-driven engineering metrics using DORA, SPACE, and Software Engineering Insights frameworks.
• Analyze and eliminate bottlenecks across CI/CD pipelines, testing systems, developer workflows, and cloud infrastructure.
• Drive measurable improvements in deployment frequency, lead time, change failure rate, MTTR, build reliability, and engineering throughput.
• Build executive-level visibility into engineering health, operational efficiency, and productivity trends.
• Continuously improve developer experience by reducing friction, cognitive load, and repetitive operational tasks.

4. Leadership & Talent Management

• Lead, mentor, and grow a globally distributed organization of engineers, technical leads, and engineering managers.
• Build and sustain a high-performance, execution-oriented engineering culture focused on ownership, innovation, humility, and operational excellence.
• Recruit and retain top engineering talent across global regions, including strong collaboration across US and India teams.
• Develop leadership pipelines and establish clear career growth frameworks for engineers and managers.
• Foster a culture of transparency, accountability, inclusion, and continuous learning.

5. AI-Native Automation & Operational Excellence

• Drive automation initiatives that eliminate repetitive manual processes across testing, deployment, operations, documentation, and developer workflows.
• Pioneer AI-assisted and agentic dev testing practices where intelligent systems proactively generate pipelines, optimize workflows, detect issues, and assist in remediation.
• Integrate AI-powered tooling into developer portals, engineering insights platforms, testing systems, and cloud optimization workflows.
• Improve release confidence through advanced automated testing, reliability engineering, and intelligent quality gates.

Core Focus Areas

Engineering Quality

• High availability and reliability engineering
• Scalable testing infrastructure and automation
• CI/CD excellence and release reliability
• Operational maturity and engineering governance

Developer Experience

• Reducing developer friction and toil
• Improving onboarding and engineering workflows
• Accelerating feedback loops and development cycles
• Building intuitive, self-service developer platforms

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 Engineering Productivity,Quality, Developer Experience, Platform Engineering, Infrastructure, DevOps, or CI/CD systems.
• Proven experience leading distributed organizations of 40–60+ engineers and managers.

Technical Expertise

• Strong background in software engineering, cloud-native architecture, CI/CD systems, distributed systems, and large-scale infrastructure.
• Deep real-world experience operating Continuous Deployment and Continuous Delivery at scale.
• Strong understanding of Kubernetes, microservices architecture, developer platforms, testing infrastructure, and release engineering.
• Practical experience with AI-powered engineering systems, intelligent 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 internal developer platforms or platform engineering organizations at enterprise scale.
• Familiarity with DORA metrics, SPACE framework, and Software Engineering Intelligence systems.
• Experience with enterprise-grade SaaS reliability, observability, and release management practices.
• Strong understanding of developer experience methodologies and engineering effectiveness programs.
• Prior experience scaling engineering systems in hyper-growth environments.