Quality System Engineer

Omnissa•Atlanta, GA

3d•$118,800 - $160,000•Hybrid

About The Position

Omnissa is seeking a Quality Systems Engineer to own product quality end-to-end, from test strategy and automation to the full lifecycle of field-reported issues that reach engineering. This is a core engineering role focused on proactive quality ownership and reactive field intelligence. The Quality Systems Engineer designs and builds test gates for product reliability, and acts as the engineering first responder for complex, high-priority field issues. They investigate, reproduce, and distill these issues into precise, engineering-ready work items. Patterns uncovered flow back into test coverage, observability improvements, and product design, creating a feedback loop between customer experience and engineering development. This role is responsible for metrics related to product health and the health of the field feedback pipeline.

Requirements

Strong software engineering foundation with the ability to read, debug, and reason across distributed systems and microservices.
Hands-on experience in software quality engineering, including test design, test automation, and defect lifecycle management.
Experience investigating production systems using logs, monitoring tools, and observability platforms.
Solid understanding of APIs, client-server architectures, and modern distributed systems.
Strong analytical and structured problem-solving ability for ambiguous, high-priority issues.
Excellent written and verbal communication skills for cross-functional work with Engineering, TPMs, and product stakeholders.

Nice To Haves

Experience in enterprise device management (UEM) domains such as Apple, Android, Windows, or similar platforms.
Familiarity with AI-assisted engineering tools (Cursor, Claude, Rovo, or equivalent).
Background in sustaining engineering, field engineering, or production systems engineering.
Experience building or owning test automation frameworks or developer productivity tooling.
Familiarity with observability platforms and structured log analysis.

Responsibilities

Design, develop, and maintain test plans, test cases, and automated test suites covering functional, regression, integration, and system-level scenarios.
Own test automation strategy and contribute to frameworks that improve coverage, speed, and reliability across release cycles.
Evaluate the product through the lens of usability and supportability, proactively surfacing gaps before they reach customers.
Participate in design and code reviews to embed quality thinking upstream in the development lifecycle.
Track and report on quality health metrics including defect escape rates, test coverage, automation pass rates, and release readiness signals.
Contribute to improvements in logging, diagnostics, and system observability that make the product easier to validate and debug.
Act as the engineering first responder for complex, high-priority issues arriving from the field, owning investigation and triage end-to-end.
Perform rapid technical analysis using logs, monitoring systems, and production data to assess severity, impact scope, and failure patterns.
Conduct deep technical debugging across distributed systems, APIs, services, and code paths to isolate and narrow suspected root causes.
Reproduce complex field issues in local or shared environments, ensuring reliable alignment with production behavior.
Enrich issue tickets with complete technical context — logs, configurations, network traces, reproduction steps, and system behavior details — so engineering teams can act without additional clarification.
Identify duplicate issues and link them to existing defects or known issues to maintain clean, accurate JIRA hygiene.
Collaborate with Core Engineering to validate hypotheses and confirm failure points through structured analysis.
Validate fixes in patches or releases and ensure proper issue closure including regression verification.
Analyze patterns across field issues and incoming customer service requests to identify systemic gaps in test coverage, observability, or product behavior.
Translate field intelligence into concrete engineering improvements: new test cases, observability instrumentation, documentation, or product design changes.
Participate in retrospectives for significant incidents and ensure findings produce durable improvements.
Partner with TPMs and Engineering leadership to track field issue SLAs and resolution progress across priority tiers.
Build and contribute to automation, scripts, and AI-assisted workflows that reduce repetitive triage work and improve engineering throughput.
Set up and maintain development and test environments required for issue reproduction and validation workflows.
Recommend and implement improvements to system observability, UX signals, and diagnostics that reduce future field issue volume.