Performance Engineer

About HCL Software

HCLSoftware, a division of HCLTech, develops, markets, sells, and supports software for AI and Automation, Data, Analytics and Insights, Digital Transformation, and Enterprise Security. HCLSoftware is the cloud-native solution factory for enterprise software and powers millions of apps at more than 20,000 organizations, including more than half of the Fortune 1000 and Global 2000 companies. HCLSoftware's mission is to drive ultimate customer success through relentless product innovation.

Experience -5+ Yrs

Location- Noida /Bangalore

Application Performance Engineering Resource

We are seeking a passionate and experienced Application performance engineering SME for the products under HCLSW AI and Intelligent Operations division. This individual will be responsible for ensuring optimal performance, scalability, and reliability of all products under AI and Intelligent Operations division. Resource will be responsible for performance guidance for architecture and design decisions and drive cultural adoption of performance-first and cost-aware engineering principles. for multiple complex systems.

Key Responsibilities:

• Demonstrated ability to manage performance engineering for multiple complex products and influence product designs to deliver superior product performance with less cost.
• Work closely with various engineering development teams to understand performance needs for various teams, establish clear objectives and plans, prioritize and manage deliverables for various product’s releases.
• Define/Develop/Identify performance benchmarks for software products and API layers while applying tools, methodologies, frameworks and analytical skills as appropriate, to conduct assessment. Strong understanding of performance benchmarks, analysis, and modeling concepts and methodology
• Identify bottlenecks in applications, databases, and infrastructure, recommend tuning and optimization.
• Conduct performance, load, and stress testing using tools like JMeter, HCL DevOps Test etc. Periodically reviewing and maintaining a detailed, working knowledge of the respective products and core functionality.
• Demonstrate command of quality assurance tools, systems analysis, profiling tools, automated test case and debugging. Integrate automated performance tests into CI/CD pipelines and Implement observability practices (logging, tracing, metrics) using tools like Dynatrace, AppDynamics, New Relic, Prometheus, Grafana.
• Support analysis and debugging of complex application, infrastructure and performance problems or enhancements.
• Apply FinOps best practices for cloud cost management and resource optimization.
• Strong understanding of enterprise infrastructure/software development and testing processes, in on-premise (compute, storage, networking) or Cloud (SaaS), and the role of performance at various stages in these processes.
• Expertise in optimizing inference latency, throughput, and cost for large language models (LLMs) like GPT, Claude, LLaMA, and multimodal models.
• Skills in context engineering, memory optimization, and retrieval strategies for agent systems. Implement autonomous performance tuning using AI-driven feedback loops and anomaly detection.

Must-Have Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in performance engineering or related roles.
• Proven track record of analyzing and resolving performance issues in complex systems.
• Software Development/QA experience in a production environment, including front-end and API development and testing
• Understanding of agent orchestration frameworks (CrewAI, DSPy, SuperOptiX) for optimizing agent workflows. Ability to measure task success rate, trajectory quality, tool usage efficiency, and latency across multi-step workflows.
• Experience with establishing Performance KPIs at both component and system level.
• Experience in testing microservices, REST based applications, Cloud native PaaS, Serverless service, Database, kubernetes layer and operating system.
• Experience with issue-tracking and agile project management systems.
• In depth Knowledge of Performance Engineering concepts such as performance testing types (Stress testing, Spike Testing, Endurance (Soak) testing, Scalability testing, Capacity testing, Performance metrics such as Response time, throughput, latency, Error rate, resource utilization etc., Bottleneck analysis, Workload modeling etc. In-depth knowledge of performance testing tools.
• Deep knowledge of GPU/TPU optimization, model parallelism, and cost-aware scaling on AWS, Azure, GCP.
• Experience in test design, plans, automation, execution, and debug.
• Identifies misalignments with goals, objectives, and work direction against the organizational strategy. Makes suggestions to course correct.
• Strong analytical and problem-solving skills.
• Excellent communication and teamwork skills.