[Hiring] Software Development Engineer @UKG

Role Description

As a Software Development 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.

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.
• Establish engineering standards for automation architecture, code quality, testability, reliability, and maintainability.
• Integrate automated quality checks, release validations, and quality gates into CI/CD pipelines while improving execution speed, parallelization, stability, diagnostics, and feedback time.
• Implement automation observability through logging, metrics, traces, dashboards, and alerts; 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 and advance common platforms and reusable engineering patterns.
• Mentor engineers and manual testers in automation, software development, DevOps, and AI-assisted engineering.

Qualifications

• 5+ years of experience in software engineering, quality engineering, DevOps, platform engineering, test automation, or a related field, with proficiency in TypeScript, JavaScript, Python, Java, C#, or a comparable language.
• Experience designing and maintaining automation frameworks, internal engineering tools, and automated workflows.
• Hands-on experience with Playwright, Selenium WebDriver, or similar browser automation technologies, as well as API, integration, contract, and end-to-end testing.
• Proficiency with Git, pull requests, code reviews, build systems, deployment workflows, and CI/CD platforms such as Azure DevOps, GitHub Actions, or Jenkins.
• Working knowledge of Docker, Kubernetes, cloud services, modern application architectures, and observability practices, including logging, metrics, tracing, dashboards, and failure diagnostics.
• Hands-on experience with Claude Code, Codex, or comparable AI coding assistants, with a working understanding of MCP, tool calling, and agentic application development.
• Ability to review, validate, and safely apply AI-generated code and automated workflows.

Preferred Qualifications

• Experience helping teams transition from manual testing or tool-specific automation to reusable, maintainable engineering solutions.
• Knowledge of performance, security, accessibility, resiliency, and production validation practices.
• Familiarity with retrieval-augmented generation, vector search, AI evaluation, and multi-agent systems.
• Experience with observability platforms such as OpenTelemetry, Azure Monitor, Application Insights, Datadog, Grafana, or Splunk.

What Success Looks Like

• Teams adopt shared automation capabilities and reusable engineering patterns, reducing flakiness, duplicated effort, and maintenance.
• CI/CD feedback becomes faster, more reliable, actionable, and easier to diagnose.
• Automation components are well designed, documented, observable, secure, and reusable.
• AI-assisted development improves productivity and failure analysis while maintaining appropriate validation, governance, security, and human oversight.
• Team members build stronger automation, programming, DevOps, and AI-engineering capabilities.