AL
AI Performance Test Architect
Artech LLC
🇺🇸 United States
On-site
4 weeks ago
- AI
- Load Testing
- JMeter
- Gatling
- k6
- Datadog
- Azure
- Dynatrace
- New Relic
- Splunk
- Grafana
- Prometheus
- Microservices
- CI/CD
- Performance Testing
- Jenkins
- Azure DevOps
- GitHub Actions
- GitLab CI
- AWS
- GCP
- Load Balancing
- Java
- Python
- Groovy
- JavaScript
- SOAP
- WebSockets
- RabbitMQ
- SQL
- NoSQL
- AI/ML
- Machine Learning
- AIOps
- Azure AI
- ChatGPT
- Copilot
- Claude
- Gemini
- Pandas
- NumPy
- scikit-learn
- Test Automation
4 weeks ago
Title: AI Performance Test Architect
Location: Tampa, FL (Onsite)
Duration: 6 months
Pay Range: $50 - $53/Hour on W2/C2C (All inclusive)​
Technical Skills:
• Load Testing Tools: Deep expertise in tools such as JMeter, LoadRunner, Gatling, k6, NeoLoad, or BlazeMeter.
• APM & Observability: Strong hands-on experience with Datadog, Azure Application Insights, and exposure to Dynatrace, New Relic, AppDynamics, Splunk, Grafana, or Prometheus.
• Bottleneck Analysis: Expert-level skills in performance bottleneck identification across CPU, memory, threads, GC, database queries, network latency, and microservices.
• CI/CD Integration: Experience integrating performance testing into pipelines using Jenkins, Azure DevOps, GitHub Actions, or GitLab CI.
• Cloud Platforms: Working knowledge of AWS, Azure, or GCP — including auto-scaling, load balancing, and cloud-native performance considerations.
• Scripting & Programming: Proficiency in Java, Python, Groovy, or JavaScript for scripting and automation.
• 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):
• 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.
• Predictive Performance Analytics: Experience using ML models for capacity forecasting, performance trend analysis, and proactive bottleneck prediction.
• 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.
• 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.
• Data & ML Foundations: Working knowledge of Python data libraries (Pandas, NumPy, Scikit-learn), time-series analysis, and basic ML concepts applied to performance datasets.
• Intelligent Test Automation: Familiarity with AI-driven approaches for self-healing test scripts, smart workload modeling, and risk-based performance test selection.
• Prompt Engineering: Ability to craft effective prompts to integrate LLMs into performance engineering workflows for analysis, recommendations, and automation.
Preferred Qualifications:
• Bachelor's or master's degree in computer science, Engineering, Data Science, or related field.
• 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.
• Experience in regulated industries (Financial Services, Healthcare, Insurance) is a plus.
• Knowledge of chaos engineering, resilience testing, and AI-driven SRE practices.
• Experience building or integrating custom ML models or LLM-based agents to support performance engineering workflows.
Company Benefits & Culture
• Opportunity to work with a dynamic team in a fast-paced environment
• Exposure to cutting-edge technologies and methodologies
• Supportive and collaborative work culture
Appreciate your quick response and please feel free to reach me out for any query you may have.
Thanks
AI Performance Test Architect · Artech LLC