Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like, where youll be supported and inspired by a collaborative community of colleagues around the world, and where youll be able to reimagine whats possible. Join us and help the worlds leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

As an Automation Tester (Performance Engineering) at Capgemini, you will design and build robust performance testing frameworks while driving end-to-end performance validation across modern, distributed systems.

You will define testing strategies, simulate real-world workloads, and ensure applications meet scalability, reliability, and performance standards.

This role requires strong expertise in performance testing tools, Python scripting, API testing, observability, and CI/CD integration, with a focus on identifying bottlenecks and optimizing system performance.

Responsibilities & Scope

• Build a robust performance testing framework from scratch (tools, standards, execution model, and reporting)
• Define performance testing strategy, workload models, and execution approaches
• Derive realistic workloads using production traffic patterns
• Analyze system architectures to identify critical APIs, dependencies, and workflows
• Develop API-based performance test scripts using:
• Gatling (Scala/Java preferred)
• JMeter / Locust
• Leverage Python (mandatory) for automation, scripting, and custom tooling
• Execute load, stress, scalability, and endurance testing
• Perform deep debugging and bottleneck analysis (latency, CPU, memory, database, network)
• Drive root cause analysis and performance tuning recommendations
• Integrate performance testing into CI/CD pipelines (Azure DevOps, Jenkins, GitHub Actions)
• Work within Azure cloud environments (App Services, AKS, Functions)
• Validate performance across microservices and distributed architectures
• Define and align NFRs, KPIs, and SLAs with stakeholders
• Evaluate and recommend performance tools and frameworks
• Design and execute reliability and chaos engineering experiments (Azure Chaos Studio, Gremlin)
• Use APM and observability tools (New Relic, Datadog, Splunk) to analyze logs, metrics, and traces
• Build dashboards and provide performance insights and reporting
• Collaborate with Dev, DevOps, and Architecture teams to optimize system performance and scalability

What youll love

Exposure to top global companies working with Capgemini (145 of the Fortune 500 companies)

Tech solutions and projects driving societal impact and paving the way for a sustainable future

Well-being hub and different wellbeing initiatives

Need to know

Career Development in Spanish & English: Training, certifications, and mentorship programs available in both languages to support bilingual growth.

Community Engagement: Participate in local volunteering initiatives, tech meetups, and cultural events that connect you with the Capgemini community.

About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.