Software Development Engineer 3

About Esper

Esper revolutionizes device management by redefining what it should be: a driver of business growth. With advanced and modern capabilities, automation replaces outdated workflows, re-provisioning becomes obsolete, and managing by exception transforms efficiency, resulting in increased efficiency, improved ROI, and bolsters security for device fleets of all sizes. Esper has been recognized as number 735 on Inc. Magazine's 2025 5000 fastest-growing private companies in America, and 133 on the 2024 Deloitte Technology Fast 500. Some of the world’s most innovative brands, like Google, Doordash, Taco Bell, Clinical ink, SF 49ers, and Intelity, rely on Esper to deliver exceptional device experiences. Esper partners with the leading mobile device hardware manufacturers, solution providers, and distributors globally.

What You'll Be Doing

- Understand product requirements, architecture, and customer workflows and design effective validation strategies.

- Build and scale API/UI automation frameworks and reusable engineering guardrails across DRE.

- Develop automated coverage for new product features, customer workflows, regressions, and production issues.

- Perform release validation and continuously reduce the manual effort required for releases.

- Move validation earlier in the SDLC by integrating automated checks into development, PR, and CI/CD workflows.

- Build developer tooling that provides fast and actionable feedback to engineering teams.

- Expand automation coverage across Windows, Linux, Airwave, and other areas with limited current coverage.

- Convert customer and requirement scenarios into reusable automated validation contracts.

- Investigate failures across UI, APIs, backend services, logs, databases, containers, devices, and environments.

- Debug backend/cloud issues and contribute code fixes when required.

- Use AI coding tools and agents to accelerate development, automation, test generation, debugging, failure analysis, and maintenance.

- Improve the reliability, maintainability, and execution speed of existing automation.

- Contribute to Hard Commits, P3s, PFRs, backend/cloud engineering, and other DRE priorities as required.

- Partner with Engineering, Product, and Release teams to improve release confidence and developer velocity.

Skills & Abilities (Required)

3–5 years of relevant software testing/automation engineering experience.

- Strong software testing fundamentals and ability to design comprehensive validation strategies.

- Strong programming fundamentals in Java, Python, JavaScript/TypeScript, Go, or equivalent.

- Hands-on API testing and API automation experience.

- Hands-on UI automation experience using Playwright, Selenium, or equivalent.

- Experience designing/building reusable automation frameworks or test infrastructure.

- Good understanding of backend systems, APIs, databases, asynchronous processing, retries, queues, and failure handling.

- Ability to read, debug, modify, and test existing backend code.

- Strong debugging/RCA skills across application, API, backend, logs, database, automation, and environment layers.

- Experience integrating automated validation into PR and CI/CD workflows.

- Git/GitHub and modern software-development workflow experience.

- Ability and willingness to use AI-assisted development tools as part of day-to-day engineering.

- Strong ownership, problem-solving, and communication skills.

Bonus Points if You Have

- Hands-on backend/cloud development experience.

- Docker/Kubernetes experience.

- SQL/database debugging.

- Windows/Linux automation.

- Device-management or enterprise SaaS experience.

- Performance, reliability, scalability, or resilience testing.

- Internal developer-tooling experience.

- Observability/logging/metrics/tracing experience.

- Experience building AI/LLM/agent-assisted engineering workflows.

What We Think Makes Us Special

 High ownership with direct impact on product and customer reliability.

- Quality is treated as an engineering responsibility rather than a downstream testing activity.

- Opportunity to influence how validation is built into the entire development lifecycle.

- Work across testing, automation, backend/cloud, device workflows, and developer tooling.

- AI-first engineering environment with opportunities to use AI for real development and quality problems.

- Ability to build reusable systems and guardrails consumed by multiple engineering teams.

- Direct impact on release confidence and engineering velocity.