Sr Software Development Engineer

At UKG, the work you do matters.

The code you ship, the decisions you make, and the care you show a customer all add up to real impact.

Today, tens of millions of workers start and end their days with our workforce operating platform.

Helping people get paid, grow in their careers, and shape the future of their industries.

That’s what we do.

We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you. UKG is seeking a highly skilled Senior Software Development Engineer (P3) to join our Shared Services team within Employee Solutions & Experience (ESE). This role is focused on advancing Quality Engineering through scalable test automation, strong software engineering practices, AI-enabled capabilities, and shared solutions that enable product teams to deliver high-quality software at speed. As a senior engineer, you will design and implement modern automation solutions, contribute to engineering and DevOps best practices, and partner closely with development teams across ESE to improve quality, test coverage, delivery efficiency, and release confidence. You will contribute to quality transformation through reusable automation frameworks, continuous testing, observability, AI-assisted development, and agentic approaches to software validation. The ideal candidate combines strong technical expertise with a passion for improving engineering processes, supporting other engineers, and building reusable solutions that benefit multiple teams across UKG. They will bring the mindset of a software engineer, with practical experience applying modern development tools, AI coding assistants, Model Context Protocol, and AI agents to improve engineering productivity and quality outcomes. ## Key Responsibilities * Design, develop, and maintain scalable test automation frameworks, libraries, shared services, and developer tools. * Build reusable capabilities for browser, API, integration, contract, performance, accessibility, and end-to-end testing. * Apply engineering standards for automation architecture, code quality, testability, reliability, and maintainability. * Integrate automated quality checks, release validations, and quality gates into CI/CD pipelines. * Improve test execution speed, parallelization, diagnostics, stability, and feedback time. * Contribute logging, metrics, traces, dashboards, and alerts to improve automation observability. * Analyze test, build, deployment, application, and production telemetry to identify quality issues. * Partner with development, DevOps, SRE, security, architecture, and release teams to improve delivery quality. * Support and mentor engineers and manual testers in automation, software development, DevOps, and AI-assisted engineering. * Contribute to common platforms and reusable engineering patterns that reduce duplicated frameworks and maintenance effort. ## Required Qualifications * 5+ years of experience in software engineering, quality engineering, DevOps, platform engineering, test automation, or a related discipline. * Strong programming skills in TypeScript, JavaScript, Python, Java, C#, or a comparable language. * Experience designing or significantly contributing to maintainable automation frameworks or internal engineering tools. * Hands-on experience with Playwright, Selenium WebDriver, or similar browser automation technologies. * Experience with API, integration, contract, and end-to-end testing. * Experience with Azure DevOps, GitHub Actions, Jenkins, or another CI/CD platform. * Practical knowledge of Git, pull requests, code reviews, build systems, and deployment workflows. * Working experience with Docker, Kubernetes, cloud services, or modern application architectures. * Knowledge of observability concepts, including logging, metrics, tracing, dashboards, and failure diagnostics. * Hands-on experience using Claude Code, Codex, or comparable AI coding assistants for software engineering work. * Working understanding of MCP, tool calling, and agentic application-development concepts. * Ability to review, validate, and safely use AI-generated code and automated workflows. * Strong analytical, communication, collaboration, and problem-solving skills. ## Preferred Qualifications * Experience contributing to shared engineering platforms or developer-productivity tools. * Experience with OpenTelemetry, Azure Monitor, Application Insights, Datadog, Grafana, or Splunk. * Knowledge of performance, security, accessibility, resiliency, or production validation. * Familiarity with retrieval-augmented generation, vector search, AI evaluation, or multi-agent systems. * Experience helping teams transition from manual testing or tool-specific automation to reusable engineering solutions. ## What Success Looks Like * Teams adopt shared automation capabilities and reusable engineering patterns. * CI/CD feedback becomes faster, more reliable, and more actionable. * Test flakiness, duplicated effort, and automation maintenance are reduced. * Automation components are well designed, documented, observable, and reusable. * AI-assisted development improves engineering productivity and failure analysis. * AI-enabled workflows operate with appropriate validation, security, governance, and human oversight. * Other team members develop stronger automation, programming, DevOps, and AI-engineering skills. The strongest candidate will think like a software engineer who specializes in quality. They should be able to demonstrate meaningful systems, frameworks, or engineering capabilities they have designed and implemented—not only tools they have used.