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Test EngineerQA Engineer – AI Platform (API Gateway & MCP Integration)

With a global team of 5600+ IT professionals, DHL IT Services connects people and keeps the global economy running by continuously innovating and creating sustainable digital solutions. We work beyond global borders and push boundaries across all dimensions of logistics. You can leave your mark shaping the technology backbone of the biggest logistics company of the world. All our offices have earned #GreatPlaceToWork certification, reflecting our commitment to exceptional employee experiences.

Digitalization. Simply delivered.

Join us at DHL Group Digital Platforms department, where innovation thrives and technology evolves. With a presence across three countries and two continents, we are building a One Stop Shop for all DHL Group APIs and AI-enabled services. Our startup spirit within a stable enterprise environment enables us to deliver secure, scalable, and modern platforms powered by Agile and DevSecOps practices.

About the Project

Be part of a strategic initiative to build DHL’s AI Enablement Platform based on Model Context Protocol (MCP), where Apigee X acts as the secure gateway connecting applications to AI-driven services.

This platform:

Provides a centralized entry point for consuming AI services through APIs
Integrates with MCP services responsible for AI orchestration and execution
Enforces security, governance, and traffic management through Apigee
Supports scalable and high-performance AI interactions across business domains

As a QA Engineer, you will play a key role in ensuring the quality, reliability, and security of the platform by validating end-to-end interactions across gateway, backend services, and AI integrations.

#DHL #DHLITServices #GreatPlace #digitalplatforms #AI #QA #MCP #APIPlatform

Grow togetherAs a QA Engineer – AI Platform, you will be responsible for ensuring the quality, reliability, security, and performance of API-driven and AI-enabled platform capabilities. You will work across API gateways, MCP, client applications, downstream integrations, and AI workflow orchestration layers.

Your responsibilities will include:

Design, document, and execute test strategies, test plans, and test cases for the Apigee API gateway, MCP Server, MCP App, and related platform components.
Test AI-related scenarios, including request and response handling, context propagation, prompt/request construction, tool invocation behavior, response validation, error handling, and fallback flows.
Validate end-to-end flows across clients, API gateway configurations, MCP server, MCP App and downstream integrations
Perform functional, integration, regression, exploratory, performance, scalability, and reliability testing for APIs and AI-driven workflows.
Develop and maintain automated test scripts for API testing using tools such as Newman, or REST Assured
Validate security implementations, including authentication, authorization, and threat protection mechanisms
Support CI/CD pipelines by integrating testing into automated delivery processes
Analyze logs and metrics to support defect investigation and continuous improvement
Work closely with engineers and architects to identify defects early and improve overall quality

Ready to embark on the journey? Here’s what we are looking for:

8+ years of experience in software testing or quality assurance, preferably in API or platform environments
Strong experience in API testing, including RESTful services and API-first design
Familiarity with API testing tools such as Newman, REST Assured, or similar
Experience validating API gateway implementations, preferably Apigee or similar platforms
Understanding of authentication and security testing, including OAuth2 and JWT
Knowledge of integration and end-to-end testing in distributed systems
Familiarity with test automation frameworks and CI/CD pipelines
Ability to analyze logs, troubleshooting issues, and collaborate effectively with engineering teams
Strong attention to detail and problem-solving skills

Nice to have:

Exposure to AI or LLM-based systems and MCP or similar architecture
Understanding of AI interaction patterns, including context handling and tool invocation
Experience with E2E tools (Playwright) for applications testing
Experience with performance testing tools such as JMeter or k6
Familiarity with observability tools, including Grafana and Prometheus
Knowledge of microservices architecture and cloud-based systems
Experience in test automation for large-scale API platforms

An array of benefits for you:

Hybrid work arrangements to balance in-office collaboration and home flexibility.
Annual Leave: 42 days off apart from Public / National Holidays.
Medical Insurance: Self + Spouse + 2 children. An option to opt for Voluntary Parental Insurance (Parents / Parent -in-laws) at a nominal premium covering pre existing disease.
In House training programs: professional and technical training certifications.