Overview
Production Engineering is seeking aSr,Software Development Engineer in Test (SDET)to drivesystem reliability, scalability, and performance validationthrough automation and engineering rigor.
This role goes beyond traditional testingyou will build systems and frameworks thatvalidateproduction readiness, enforceperformance and reliability standards, and ensure services behave correctly under real-world conditions.
You willoperateat the intersection of software engineering, performance engineering, and system reliability, driving the strategy, architecture, and implementation of validation frameworks that ensure services are reliable, scalable, andproduction-ready.
Key Responsibilities
System Validation & Test Automation
- Build andmaintainautomated validation frameworksfor APIs, distributed systems, and critical service workflows
- Developintegration and end-to-end validation suitesthat reflect real production use cases
- Ensure validation isfully integrated into CI/CD pipelineswith meaningful quality gates
- Design systems and tooling that improvetestability, observability, and diagnosability
- Drive improvements in validation coverage and overall system confidence through data-driven analysis and risk-based prioritization
- Drive reduction of flaky or low-signal tests to ensurehigh signal-to-noise automation
Performance Engineering
- Design and implementload, stress, and endurance testing strategiesfor distributed systems
- Build andmaintainperformance test frameworks and workloadsthat model real traffic patterns
- Define andmaintainperformance baselines, SLAs/SLOs, and capacity models that guide engineering and operational decisions
- Analyze system behavior under load toidentifybottlenecks, resource contention, and scaling limits
- Drive performance improvements by working directly in code, configuration, and infrastructure
- Integratecontinuous performance validationinto CI/CD and pre-production workflows
Production Engineering & Reliability
- Ensure services meetproduction readiness standards, including reliability, scalability, and observability
- Improve system confidence byvalidatingreal-world scenarios, edge cases, and degradation paths
- Advocate for engineering practices that improveoperability and system robustness
- Drive reliability validation efforts for complex distributed systems, including resilience, failover, and recovery testing
- Influence system architecture by advocating for reliability, observability, and operability best practices
- Use production telemetry and incident learnings to continuously improve validation and performance strategies
Required Qualifications
- Bachelors degree in Computer Science, Engineering, or related field
- 6 6years of experiencein software engineering, SDET,SREor related roles
- Strong programming skills (Java, Python, C#, or JavaScript) with ability to build production-quality code
- Proven experience designing and implementing scalable automation frameworks or validation platforms
- Hands-on experience withAPI and distributed systems testing
- Experience withperformance testing tools(e.g., k6, JMeter, Gatling)
- Familiarity withCI/CD systemsand modern development workflows
- Solid understanding ofsystem design, scalability, and performance fundamentals
Preferred Qualifications
- Experience inProduction Engineering, SRE, or infrastructure-focused teams
- Familiarity withmicroservices and cloud-native architectures
- Experience withobservability tools(e.g., metrics, logs, tracing1Grafana, Prometheus, Datadog)
- Knowledge ofcontainers and orchestration(Docker, Kubernetes)
- Exposure toresilience testing, chaos engineering, or fault injection
- Experience modelingproduction traffic patterns or capacity planning
Key Skills
- Strong systems-thinking mindset with deep understanding of distributed system behavior under load and failure conditions
- Ability to lead complex technical initiatives with minimal direction
- Strong technical judgment and ability to balance reliability, performance, and engineering velocity
- Experience influencing engineering teams through technical leadership and collaboration
- Exceptional troubleshooting and root-cause analysis skills
What Success Looks Like
- Systems arevalidatedagainstrealistic production scenarios, not just functional correctness
- Improved system reliability throughproactive validation of edge cases and failure modes
- Strong contribution to a culture ofengineering ownership of quality and performance
- Performance and scalability risks areidentifiedand mitigated early in the development lifecycle
- Validation frameworks become trusted engineering tools used across teams
- Reliability, performance, and production-readiness standards are consistently met across supported services
- Engineering teams proactivelyleveragevalidation and performance insights to improve system design
