The posting
Job Description:
We are Omnissa!
Omnissa is the first AI-driven digital work platform, built to support flexible, secure, work-from-anywhere experiences. We integrate industry-leading solutions—including Unified Endpoint Management, Virtual Apps and Desktops, Digital Employee Experience, and Security & Compliance into a seamless, autonomous workspace that adapts to how people work. Our platform boosts employee engagement while optimizing IT operations, security, and cost.
Guided by our Core Values Act in Alignment, Build Trust, Foster Inclusiveness, Drive Efficiency, and Maximize Customer Value, we’re growing rapidly and committed to delivering meaningful impact. If you're passionate about shaping the future of work, we’d love to hear from you.
What is the opportunity?
We are seeking a Frontline Engineer (MDM and Quality Systems Side of Experience is Mandate) 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, not a support function. It sits at the intersection of proactive quality ownership and reactive field intelligence, treating every real-world issue as a signal that strengthens the system.
Quality Systems Engineers design and build the test gates that keeps the product reliable. They also serve as the engineering first responder when complex, high-priority issues arrive from the field — investigating, reproducing, and distilling them into precise, engineering-ready work items. Critically, the patterns they uncover flow back into test coverage, observability improvements, and product design, closing the loop between what customers experience and what engineering builds next.
This role owns metrics across two dimensions: the health of the product as measured through traditional quality indicators, and the health of the field feedback pipeline as measured through incoming service request volume, field issue triage velocity, and the rate at which systemic issues are eliminated. Both dimensions matter equally.
Key Responsibilities
- Test Strategy & Quality EngineeringDesign, 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 — not just correctness — and proactively surface 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
- Field Issue Investigation & Engineering TriageAct 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 (e.g., Logz.io: Modern Observability Powered by AI ), 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
- Systemic Quality Improvement & Feedback LoopAnalyze 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 — not just one-time fixes 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
Required Qualifications
- 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
Preferred Qualifications
- 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
Key Performance Indicators (KPIs)
- Field Health & Issue PipelineVolume and trend of incoming customer service requests over time Volume and trend of field issues routed to engineering for investigation Time to first technical assessment of field issues SLA compliance for high-priority field issues Successful reproduction rate of customer-reported issues Time to identify root cause or failure domain Percentage of issues fully enriched and ready for engineering action without follow-up Number of recurring issue patterns eliminated through systemic improvements
- Product QualityDefect escape rate and regression rate across releases Test automation coverage and pass rate Reduction in duplicate defects and improved JIRA hygiene Contributions to logging, observability, or test coverage that measurably reduce field issue volume Release readiness signal accuracy — how well pre-release quality metrics predict post-release stability
Why This Role Matters
Most engineering organizations treat product quality and field issue response as separate concerns, handled by separate teams. Quality Systems Engineers reject that separation. They own both and in owning both, they create something neither function can create alone, a continuous, closed-loop system where real-world customer experience directly shapes what gets tested, what gets instrumented, and what gets built next.
The result is compounding: field issues get resolved faster, the same issues stop recurring, and the product becomes measurably more stable with every release cycle. This is quality engineering operating at its highest level of impact.
Location:India (Bangalore) Location Type: HYBRID Travel Expectations: Yes Education: Bachelor's Degree or equivalent combination of education and relevant professional experience.
