Senior Performance Engineer

Cloud Bees helps organizations build, run, and govern software factories, giving enterprises the confidence to ship software better, faster, and safer.

Writing code is no longer the bottleneck. Governing what reaches production and validating its impact is. As enterprises adopt agentic coding, software is created faster than most teams can review, secure, and validate. Without consistent governance, organizations risk shipping code they cannot explain, audit, or trust.

Cloud Bees addresses this challenge without asking teams to replace the tools they already use. Across every toolchain a customer runs, Cloud Bees makes each change, human or AI, visible, auditable, and accountable before it reaches production. Cloud Bees Unify is the product behind this: a governance layer, with context and control-plane capabilities, that enforces consistent policy and evidence across every tool, team, and workflow.

Founded in 2010, Cloud Bees is backed by Goldman Sachs, Morgan Stanley, Bridgepoint Capital, HSBC, Golub Capital, Delta-v Capital, Matrix Partners, and Lightspeed Venture Partners.

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Cloud Bees is evolving its quality engineering model around automated testing, and this role will help define how performance, scalability, and reliability are engineered into our products from the start. As a Senior Performance Engineer, you will build performance testing as code, establish measurable baselines and quality gates, and partner with engineering teams to identify and resolve bottlenecks before they reach customers.

You will combine hands-on software engineering, systems thinking, and production telemetry to help Cloud Bees ship software faster without compromising trust, resilience, or customer experience.

• Design and own the performance engineering strategy for the products and distributed services in your domain.
• Build and maintain automated load, stress, spike, soak, scalability, and resilience tests as version-controlled code.
• Integrate performance tests, thresholds, and regression detection into CI/CD workflows at the appropriate stage of the delivery process.
• Partner with service owners and SRE to define meaningful performance baselines, service-level objectives, and release criteria across latency, throughput, error rates, resource use, and scalability.
• Diagnose performance bottlenecks using observability data, profiling, tracing, logs, metrics, and disciplined experimentation.
• Partner with software engineers, architects, SRE, product, and platform teams to design for performance early in the development lifecycle.
• Create realistic, repeatable test environments, workloads, data sets, and capacity models for cloud-native systems.
• Develop dashboards and automated reporting that make performance trends, regressions, and risks visible to engineering leaders.
• Improve performance engineering practices, tooling, documentation, and technical standards across teams.
• Coach engineers on performance testing, measurement, root-cause analysis, and automated quality practices.
• Use AI coding agent (Claude code or similar) to build and maintain test suites, generate workloads, and analyze results and apply judgement to what they produce.

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• 7+ years of experience in software engineering, performance engineering, site reliability engineering, or a closely related discipline, including substantial hands-on performance testing experience
• Strong software development skills in at least one language such as Java, Go, Python, or JavaScript/Type Script
• Hands-on experience with performance and load-testing tools such as k6, Gatling, JMeter, Locust, or equivalent
• Experience automating tests and quality gates in modern CI/CD pipelines
• Strong knowledge of distributed systems, APIs, microservices, containers, Kubernetes, and cloud infrastructure
• Experience analyzing latency, throughput, concurrency, error rates, resource saturation, and capacity limits
• Experience using observability and profiling tools to isolate bottlenecks across application, database, network, and infrastructure layers
• Ability to translate business-critical user journeys and reliability expectations into realistic workloads, measurable thresholds, and actionable engineering…