Job Description - AI Performance Test EngineerJob Title: Model Performance Test Engineer / Performance Test Engineer (AI Platforms)Experience: 7-14 YearsWork Location: Pune (Onsite)Notice Period: Immediate to Short Notice PreferredJob SummaryWe are looking for an experienced AI Performance Test Engineer to evaluate the performance, scalability, reliability, and stability of AI agents, Generative AI applications, and AI platforms. The ideal candidate should have strong expertise in performance testing tools, workload modeling, bottleneck analysis, and performance engineering, along with a solid understanding of AI/LLM-based applications and their performance characteristics.
Key Responsibilities- Design and execute performance, load, stress, endurance, and scalability tests for AI agents and AI platforms.
- Develop performance test strategies, scenarios, and workload models based on business and technical requirements.
- Analyze application performance and identify bottlenecks across APIs, databases, infrastructure, and AI services.
- Monitor CPU, memory, network, storage, and application performance metrics.
- Validate response times, throughput, concurrency, and resource utilization under varying workloads.
- Work closely with developers, architects, DevOps, and AI/ML teams to resolve performance issues.
- Prepare detailed performance reports with observations and optimization recommendations.
- Support performance tuning and capacity planning activities.
- Integrate performance testing into CI/CD pipelines where applicable.
- Ensure AI applications meet defined SLAs and performance benchmarks.
Mandatory Skills- 7-12 years of experience in Performance Testing and Performance Engineering.
- Hands-on experience with LoadRunner, JMeter, Gatling, or similar performance testing tools.
- Strong understanding of performance testing methodologies including Load, Stress, Spike, Soak, and Endurance Testing.
- Experience testing REST APIs, microservices, and distributed applications.
- Knowledge of monitoring tools such as Dynatrace, AppDynamics, Grafana, Prometheus, Splunk, or New Relic.
- Experience analyzing performance bottlenecks using logs, metrics, and profiling tools.
- Good understanding of AI Agents, Generative AI, LLM-based applications, or AI platforms.
- Familiarity with AI inference performance metrics such as latency, throughput, concurrency, and token processing.
- Strong SQL and troubleshooting skills.
