Performance Testing and Engineering Architect

Infosys; Chennai, Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Infosys is seeking a senior performance engineering leader in Chennai to drive architecture-level testing strategies and enterprise-scale solution design. You will lead technical teams, define NFR models, and guide performance transformation across cloud-native, distributed systems while leveraging AI/Generative AI testing approaches.

Candidate should have hands-on expertise with APM tools, CI/CD, Docker/Kubernetes, and strong client-facing communication to present RFP/RFI responses and delivery

Qualifications

• Proven experience defining enterprise performance engineering strategies, NFR models, reusable frameworks and performance-tuning recommendations.
• Architecture-level knowledge of more than two performance test tools, with practical exposure to both enterprise and open-source platforms.
• Hands-on experience with at least two APM/observability platforms and the ability to correlate logs, metrics and traces with performance results.
• Strong hands-on capability in thread dump analysis, heap dump analysis, garbage collection analysis, JVM/application diagnostics and infrastructure bottleneck analysis.
• Ability to design reusable utilities, accelerators or framework extensions using Python, Java or an equivalent programming language.
• Experience with CI/CD, Git, Docker, Kubernetes, cloud-based execution and distributed systems.
• Experience anchoring RFP/RFI responses, architecting solutions, estimating delivery scope and presenting to senior client stakeholders.
• Experience assessing process maturity and driving performance engineering transformation, governance and continuous improvement.
• Practical exposure to generative AI or agentic AI performance testing, including multi-turn workload modelling and AI-specific performance measures.
• Demonstrated ability to lead by example, mentor and coach engineers, and build high-performing technical teams.
• Strong systems thinking, analytical problem-solving, stakeholder influence, documentation, presentation and consulting skills.
• At least one relevant current cloud certification from AWS, Microsoft Azure or Google Cloud, and at least one recognized AI/Generative AI certification.
• Hands-on experience with Chaos Engineering concepts, GameDay execution and resilience validation methodologies.
• Experience designing and executing failure injection scenarios across cloud-native, microservices and distributed architectures.
• Strong understanding of SRE principles including SLIs, SLOs, Error Budgets, Reliability Engineering and Incident Management.
• Demonstrated ability to analyze resilience test results and drive architecture improvements.
• Hands-on experience in client-side performance analysis, Core Web Vitals optimization, Real User Monitoring (RUM), browser diagnostics and Digital Experience Monitoring (DEM) platforms.

Skills

Performance engineering

Architecture leadership

NFR models

Performance test tools

Python

Java

CI/CD

Git

Docker

Kubernetes

Cloud platforms

AI/Generative AI

Education

Cloud certification (AWS/Azure/GCP)

AI/Generative AI certification

Tools

Git

Docker

Kubernetes

Cloud platforms

Job description

Must-Have Qualifications

• 13+ years of experience in Quality Engineering, Performance Testing or Performance Engineering, including significant architecture, solutioning and technical leadership responsibilities.
• Proven experience defining enterprise performance engineering strategies, NFR models, reusable frameworks and performance-tuning recommendations.
• Architecture-level knowledge of more than two performance test tools, with practical exposure to both enterprise and open-source platforms.
• Hands-on experience with at least two APM/observability platforms and the ability to correlate logs, metrics and traces with performance results.
• Strong hands-on capability in thread dump analysis, heap dump analysis, garbage collection analysis, JVM/application diagnostics and infrastructure bottleneck analysis.
• Ability to design reusable utilities, accelerators or framework extensions using Python, Java or an equivalent programming language.
• Experience with CI/CD, Git, Docker, Kubernetes, cloud-based execution and distributed systems.
• Experience anchoring RFP/RFI responses, architecting solutions, estimating delivery scope and presenting to senior client stakeholders.
• Experience assessing process maturity and driving performance engineering transformation, governance and continuous improvement.
• Practical exposure to generative AI or agentic AI performance testing, including multi-turn workload modelling and AI-specific performance measures.
• Demonstrated ability to lead by example, mentor and coach engineers, and build high-performing technical teams.
• Strong systems thinking, analytical problem-solving, stakeholder influence, documentation, presentation and consulting skills.
• At least one relevant current cloud certification from AWS, Microsoft Azure or Google Cloud, and at least one recognized AI/Generative AI certification.
• Hands-on experience with Chaos Engineering concepts, GameDay execution and resilience validation methodologies.
• Experience designing and executing failure injection scenarios across cloud-native, microservices and distributed architectures.
• Strong understanding of SRE principles including SLIs, SLOs, Error Budgets, Reliability Engineering and Incident Management.
• Demonstrated ability to analyze resilience test results and drive architecture improvements.
• Hands-on experience in client-side performance analysis, Core Web Vitals optimization, Real User Monitoring (RUM), browser diagnostics and Digital Experience Monitoring (DEM) platforms.