Senior Software Engineer - Developer Experience

Be the one building AI-powered experiences where they matter most.

At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.

Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day.

The Senior Software Engineer - Developer Experience is a hands-on individual contributor focused on improving how engineers build, test, and deliver software across Genesys. You will design and deliver scalable tooling, automation, and development workflows that reduce friction, increase delivery velocity, and improve software quality. You will also help advance Genesys's AI-enabled software development lifecycle (AI-SDLC), applying sound technical judgment as AI capabilities and engineering practices evolve. This role has no direct reports; you will lead through technical ownership, mentorship, and collaboration.

· Design and deliver internal developer platforms, CI/CD pipelines, and reusable tooling that streamline code development, testing, and deployment workflows.

· Build and improve standardized development environments and paved workflows using GitHub, CI/CD automation, and testing frameworks to reduce setup time and inconsistencies across partner teams.

· Improve developer onboarding and day-to-day productivity by creating self-service capabilities, documentation, and paved paths for common engineering tasks.

· Implement and continuously improve AI-enabled software development practices, evaluating emerging capabilities and incorporating effective approaches into development, testing, and delivery workflows while maintaining quality, security, and reliability.

· Automate build, test, and release processes across the software development lifecycle to reduce manual effort, improve consistency, and shorten delivery cycles.

· Use software delivery and quality metrics, including build success rates, test effectiveness, lead time, deployment frequency, and change failure rate, to identify bottlenecks, prioritize improvements, and measure impact.

· Contribute to technical design and reusable frameworks for developer tooling and platforms, balancing developer usability, scalability, security, and operational reliability.

· Partner with platform, security, and application teams to deliver developer experience improvements aligned with enterprise standards and engineering needs, and support adoption by gathering feedback and iterating based on usage and impact.

· Mentor engineers through code and design reviews, pairing, and knowledge sharing to strengthen engineering practices within the team and partner teams.

· Demonstrated understanding of how AI is changing software development, with the ability to evaluate emerging tools and practices, learn rapidly as capabilities evolve, and apply effective approaches to engineering workflows.

· Strong hands-on software engineering experience using Python, Java, or another modern programming language, with demonstrated experience designing and delivering production-quality software or developer tooling.

· Experience in developer productivity, DevOps, or platform engineering, with a track record of delivering complex technical initiatives and contributing to cross-team efforts.

· Strong experience with CI/CD systems, version control, automated testing frameworks, and cloud-native development environments (preferably AWS) or infrastructure projects.

· Experience using software delivery metrics such as deployment frequency, lead time, build reliability, or change failure rate to identify and improve engineering workflows.

· Ability to influence adoption of tools and practices through collaboration, technical judgment, clear communication, and effective partnership across engineering teams.

· Experience with developer infrastructure, observability, and testing technologies such as GitHub, Terraform, Honeycomb, Gremlin, Playwright, or comparable tools.

· Experience integrating AI-powered developer tools, code assistants, agents, or automation capabilities into engineering workflows.

· Experience working in large-scale SaaS or distributed engineering organizations.

If you bring many of these capabilities but do not meet every qualification listed, we encourage you to apply. We value demonstrated ability, sound engineering judgment, and the capacity to learn as technologies and practices evolve.

· Reduces developer friction and cycle time across development, testing, and release workflows through automation, self-service capabilities, and paved paths.

· Improves software delivery and quality indicators such as build reliability, lead time, deployment frequency, and change failure rate within supported engineering workflows.

· Expands effective adoption of standardized and AI-enabled development practices, helping engineering teams use emerging capabilities responsibly while maintaining quality, security, and reliability.

• AI at enterprise scale – Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+ new AI features were released in the last fiscal year.
• A flexible-first culture – Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
• Growth in the AI era – Build f