Job Summary

Hybrid Mode

Immediate Joiner Only

Experience:-7-12 Years

Location:- Pune

We are seeking a Performance Engineer with robust experience in AI agents, AI platforms, distributed systems, and performance engineering to design, execute, and optimize performance testing for next-generation AI applications. The ideal candidate will have hands-on experience testing LLM-based applications, AI agent workflows, APIs, microservices, cloud platforms, and high-scale distributed systems.

Key Responsibilities

- Design and implement performance, load, stress, scalability, endurance, and capacity testing strategies for AI agents and AI platforms.
- Develop performance test plans, workload models, test scenarios, and acceptance criteria for LLM and AI-powered applications.
- Test AI agent workflows involving LLMs, RAG, vector databases, tools, APIs, memory, orchestration, and multi-agent systems.
- Measure and optimize latency, throughput, concurrency, scalability, resource utilization, availability, and reliability.
- Analyze LLM inference latency, token throughput, time-to-first-token (TTFT), time-per-output-token (TPOT), request latency, and cost/performance metrics.
- Build automated performance testing frameworks using tools such as JMeter, Gatling, Locust, k6, or custom Python-based frameworks.
- Generate realistic workloads for concurrent users, API requests, AI agent sessions, prompts, tokens, and multi-step agent workflows.
- Conduct performance testing of REST APIs, GraphQL APIs, microservices, event-driven systems, and asynchronous workloads.
- Profile applications and identify performance bottlenecks across application, database, network, infrastructure, model-serving, and cloud layers.
- Monitor and analyze systems using Prometheus, Grafana, ELK/OpenSearch, Datadog, New Relic, CloudWatch, Azure Monitor, or equivalent tools.




- Evaluate performance of AI infrastructure including GPU/CPU utilization, memory, network throughput, model serving, autoscaling, and containerized workloads.
- Collaborate with AI/ML engineers, software engineers, DevOps, SRE, architects, and product teams to resolve performance issues.
- Establish performance baselines, SLAs, SLOs, KPIs, capacity thresholds, and performance regression criteria.
- Integrate performance tests into CI/CD pipelines and support continuous performance monitoring.
- Perform root-cause analysis and provide actionable recommendations for improving AI platform scalability, reliability, and efficiency.
- Prepare performance reports, dashboards, bottleneck analysis, capacity forecasts, and executive-level performance summaries.

Required Skills
- 4+ years of experience in performance engineering, performance testing, load testing, or scalability engineering.
- Hands-on experience testing AI/ML applications, LLM applications, AI agents, or AI platforms.
- Strong understanding of distributed systems, microservices, APIs, cloud computing, and scalable architectures.
- Experience with performance testing tools such as JMeter, Gatling, Locust, k6, LoadRunner, or similar.
- Strong programming/scripting skills in Python, Java, JavaScript, or similar languages.
- Experience with REST APIs, JSON, HTTP, WebSockets, asynchronous processing, and API performance testing.
- Strong knowledge of Linux, networking, databases, caching, queues, and system performance concepts.
- Experience with observability and monitoring tools such as Prometheus, Grafana, ELK, Datadog, New Relic, or cloud-native monitoring solutions.
- Experience with Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
- Strong analytical and troubleshooting skills with the ability to identify performance bottlenecks and root causes.

AI/LLM Performance Skills

📌 Performance Tester (Pune)
🏢 Innova ESI
📍 Pune