Information Technology_USA - USA_Developer job in Jacksonville
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Job description
**Please strictly adhere to the following resume naming convention:ALL CAPS, NO SPACES B/T UNDERSCORESPTN_US_GBAMSREQID_CandidateBeelineIDi.e. PTN_US_9999999_SKIPJOHNSON0413MSP Owner: Tory RobinsonMax : /hrLocation: Tampa, FL - OnsiteDuration: 6 MonthsGBaMS ReqID: 10960284AI Performance Test ArchitectTechnical Skills&bull Load Testing Tools: Deep expertise in tools such as JMeter, LoadRunner, Gatling, k6, NeoLoad, or BlazeMeter.&bull APM & Observability: Strong hands-on experience with Datadog, Azure Application Insights, and exposure to Dynatrace, New Relic, AppDynamics, Splunk, Grafana, or Prometheus.&bull Bottleneck Analysis: Expert-level skills in performance bottleneck identification across CPU, memory, threads, GC, database queries, network latency, and microservices.&bull CI/CD Integration: Experience integrating performance testing into pipelines using Jenkins, Azure DevOps, GitHub Actions, or GitLab CI.&bull Cloud Platforms: Working knowledge of AWS, Azure, or GCP - including
Requirements
auto-scaling, load balancing, and cloud-native performance considerations.&bull Scripting & Programming: Proficiency in Java, Python, Groovy, or JavaScript for scripting and automation.&bull Protocols & Architectures: Strong understanding of HTTP/HTTPS, REST/SOAP APIs, WebSockets, microservices, message queues (Kafka, RabbitMQ), and database performance (SQL/NoSQL).AI/ML & GenAI Skills (Required)&bull AI-Powered Observability: Hands-on experience with AIOps platforms and AI-driven APM features such as Datadog Watchdog/Bits AI, Dynatrace Davis AI, New Relic AI, or Azure AI Anomaly Detector.&bull Predictive Performance Analytics: Experience using ML models for capacity forecasting, performance trend analysis, and proactive bottleneck prediction.&bull Anomaly Detection & Root Cause Analysis (RCA): Ability to design or leverage AI/ML models for automated anomaly detection, intelligent alerting, noise reduction, and AI-assisted RCA.&bull Generative AI for Engineering Productivity: Practical experience using GenAI tools (ChatGPT, Copilot, Claude, Gemini) for automated script generation, test data creation, log/trace summarization, and intelligent reporting.&bull Data & ML Foundations: Working knowledge of Python data libraries (Pandas, NumPy, Scikit-learn), time-series analysis, and basic ML concepts applied to performance datasets.&bull Intelligent Test Automation: Familiarity with AI-driven approaches for self-healing test scripts, smart workload modeling, and risk-based performance test selection.&bull Prompt Engineering: Ability to craft effective prompts to integrate LLMs into performance engineering workflows for analysis, recommendations, and automation.Preferred Qualifications&bull Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.&bull Industry certifications in performance engineering, cloud platforms (AWS/Azure), APM tools (Datadog, Dynatrace), or AI/ML certifications (Azure AI Engineer, AWS ML Specialty, Google ML Engineer) is a plus .&bull Experience in regulated industries (Financial Services, Healthcare, Insurance) is a plus.&bull Knowledge of chaos engineering, resilience testing, and AI-driven SRE practices.&bull Experience building or integrating custom ML models or LLM-based agents to support performance engineering workflows.Role Descriptions: AI Performance Test ArchitectEssential Skills: AI Performance Test ArchitectDesirable Skills: Keyword: Skills: AI and AutomationExperience Required: 4-6
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