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Bengaluru, Karnataka, India
Hybrid
Job Description:
We are Omnissa!
The world is evolving fast, and organizations everywhere—from corporations to schools—are under immense pressure to provide flexible, work-from-anywhere solutions. They need IT infrastructure that empowers employees and customers to access applications from any device, on any cloud, all while maintaining top-tier security. That’s where Omnissa comes in.
The Omnissa Platform is the first AI-driven digital work platform that enables smart, seamless and secure work experiences from anywhere. It uniquely integrates multiple industry-leading solutions including Unified Endpoint Management, Virtual Apps and Desktops, Digital Employee Experience, and Security & Compliance through common data, identity, administration, and automation services. Built on the vision of autonomous workspaces—self-configuring, self-healing, and self-securing—Omnissa continuously adapts to the way people work, delivering personalized and engaging employee experiences while optimizing security, IT operations, and costs. We are experiencing rapid growth—and this is just the beginning of our journey.
At Omnissa, we’re driven by a shared mission to maximize value for our customers. Our five Core Values guide us: Act in Alignment, Build Trust, Foster Inclusiveness, Drive Efficiency, and Maximize Customer Value—all with the aim of achieving shared success for our clients and our team.
As a global private company with over 4,000 employees, we’re always looking for passionate, talented individuals to join us. If you're ready to make an impact and help shape the future of work, we’d love to hear from you.
As a Sr. Performance Engineer, you will become part of an experienced engineering team which is building a large-scale UEM platform as a service. You and your team will be responsible for identifying and delivering solutions to performance, scalability, efficiency, and capacity bottlenecks within UEM platform/services. Within your first 30 days of joining our team, you will not only acquire a fundamental understanding of the product's architecture and primary operational procedures, but also a strong understanding of performance baselines, workload patterns, and performance testing and monitoring tools used within the product.
Utilize your knowledge in .NET Framework and .NET Core web services for performance analysis, profiling, and optimization of production systems.
Work with cross-functional teams in the organization to define performance benchmarks, KPIs, and SLOs, and drive continuous performance improvements against them.
Identify, analyze, and eliminate performance bottlenecks across application, infrastructure, and database layers.
Design and execute performance, load, stress, and endurance tests to validate system behavior under varying workloads.
Respond to performance-related incidents and escalations and help prioritize engineering work, from large initiatives to sprint tasks.
Build automation tools that enable performance testing, benchmarking, capacity planning, and continuous performance validation.
Strong expertise in Application Development and software engineering, with hands-on experience in C#, Java, Go, Groovy, or Python, with a focus on performance profiling and optimization.
Hands-on experience with cloud and infrastructure technologies: AWS, vSphere, Google Cloud Platform; deep understanding of network protocols, Linux/Unix system internals, and system performance tuning; CI/CD tools such as GitHub Actions and Artifactory; Infrastructure as Code and configuration management tools like Terraform, Helm, Chef, and Salt; infrastructure domains such as Network, Database, Server, and Storage; operating systems (Linux and Windows).
Experience with performance monitoring, observability, and profiling tools to analyze system behavior and identify bottlenecks: Dynatrace, Grafana, Prometheus, Wavefront, Kibana, Logz.io, dotTrace/dotMemory, SentryOne.
Strong experience in performance engineering practices including load testing, workload modeling, profiling, benchmarking, and capacity planning.
Experience with AI/ML tools such as PyTorch, TensorFlow, Z-Scoring techniques, and LLMs for advanced analysis and anomaly detection is a plus.
Willingness to support performance validation during releases and assist in critical performance incident scenarios when needed.
