Senior Performance Test Engineer

Kforce has a client that is seeking a remote Senior Performance Test Engineer to join their team. Overview: As our infrastructure evolves, the engineer must demonstrate a progressive, adaptive mindset to actively bridge traditional on-premises data centers with modern containerized cloud environments. Advanced expertise in safeguarding high-volume architectures-specifically IBM Sterling OMS-is highly desirable to proactively prevent production incidents, maximize continuous availability, and guarantee zero-downtime retail operations. Additionally, candidates must be future-ready: either already possessing AI-driven engineering skills (such as AI-assisted code profiling or predictive anomaly detection) or demonstrating a strong willingness and agility to learn on-the-run through our upcoming enterprise AI training programs. Core Responsibilities:

• Peak Volume Modeling: Design and execute workload models based on retail metrics
• Hybrid Infrastructure Testing: Validate system performance across physical on-prem hardware and containerized cloud platforms
• Resiliency Engineering: Identify and resolve database deadlocks, row-locking, and thread contention to ensure absolute zero-downtime
• Bottleneck Diagnosis & AI Observability: Leverage traditional APM tools, log aggregators, and emerging AI-powered predictive analytics tools to isolate code, database, and network-level performance degradation
• Continuous Learning: Actively participate in internal AI up-skilling initiatives to integrate generative AI and machine learning into performance testing automation
• Seeking a senior-level Performance Engineer with 7 to 10 years of dedicated experience designing, executing, and optimizing performance testing strategies across complex enterprise IT systems
• The ideal candidate brings a proven track record of managing peak-volume and holiday-season load testing to guarantee system consistency, resilience, and architectural stability under extreme traffic

• Programming & Scripting: Java, Python, Groovy, Bash/Shell, JavaScript
• Load Generation Tools: Neoload, Apache JMeter, Gatling, BlazeMeter, LoadRunner/Performance Center
• APM & Distributed Tracing: Dynatrace, AppDynamics, Datadog, New Relic
• Log Analytics & Observability: BigQuery, Splunk, ELK Stack (Elasticsearch, Logstash, Kibana), Prometheus, Grafana
• Databases & Messaging: Oracle DB, DB2, PostgreSQL, IBM MQ, Apache Kafka, RabbitMQ
• Cloud & CI/CD Pipelines: Red Hat OpenShift, Kubernetes, Docker, Jenkins, GitLab CI, Ansible, Terraform