Senior Staff Engineer (Google Apigee Development)

👋🏼We're Nagarro. We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at a scale — across all devices and digital mediums, and our people exist everywhere in the world (18500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Requirements - Experience : 7.5+ years - Strong hands-on experience in Google Apigee API development and API management, including API proxies, policies, shared flows, and backend integrations. - Strong Python programming skills, including application development, debugging, testing, and performance optimization. - Practical experience using AI-powered coding agents such as Claude Code, GitHub Copilot, or equivalent agentic development tools. - Good understanding of REST APIs, API security, authentication, authorization, and enterprise integration patterns. - Experience implementing API security mechanisms such as OAuth 2.0, JWT, API keys, and access control. - Good understanding of API traffic management, rate limiting, quotas, caching, API governance, versioning, and lifecycle management. - Experience developing RESTful APIs and backend services using Python frameworks such as FastAPI, Flask, or Django. - Strong understanding of HTTP protocols, JSON/XML payloads, synchronous and asynchronous integration patterns, timeouts, retries, idempotency, and error handling. - Experience with Git, CI/CD pipelines, automated testing, and software development best practices. - Ability to review and validate AI-generated code for correctness, security, performance, and maintainability. - Ability to independently troubleshoot complex technical issues across API gateways, backend services, and multiple integration layers. - Strong software engineering fundamentals, analytical thinking, problem-solving, communication, and collaboration skills. - Ability to understand existing codebases, make sound technical decisions, and deliver maintainable enterprise solutions. - Experience with Apigee X or Apigee Hybrid would be an advantage. - Familiarity with Google Cloud Platform (GCP) and cloud-native application development would be beneficial. - Exposure to Docker, Kubernetes, and microservices architecture would be an added advantage. - Familiarity with MCP (Model Context Protocol), tool calling, and agentic AI development workflows would be beneficial. - Experience integrating AI coding agents into enterprise development environments with appropriate security and governance controls would be an advantage. - Familiarity with automated security scanning, API observability, performance testing, GitHub Actions, or Jenkins would be beneficial. Responsibilities - Design, develop, deploy, and maintain enterprise APIs using Google Apigee. - Develop and manage Apigee API proxies, shared flows, policies, and reusable integration components. - Implement API security mechanisms, including OAuth 2.0, JWT, API keys, authentication, authorization, and access control. - Configure API traffic management features such as rate limiting, spike arrest, quotas, caching, and fault handling. - Manage API products, developer applications, environments, deployments, versioning, and API lifecycle activities. - Design and develop scalable, robust, and maintainable applications and integration services using Python. - Build RESTful APIs and backend services using frameworks such as FastAPI, Flask, or Django. - Develop reusable Python modules, integration libraries, automation scripts, and data transformation components. - Implement asynchronous processing, exception handling, logging, monitoring, and performance optimization. - Leverage AI-powered coding agents such as Claude Code, GitHub Copilot, and similar tools for code generation, refactoring, debugging, test automation, code reviews, and technical documentation. - Design effective prompts and workflows to guide AI coding agents in solving complex engineering problems and navigating existing codebases. - Review and validate AI-generated code for correctness, security, performance, maintainability, and adherence to engineering standards. - Integrate AI-assisted development practices into existing engineering workflows and CI/CD pipelines. - Apply enterprise integration patterns involving REST APIs, HTTP protocols, JSON/XML payloads, request/response transformations, and error-handling mechanisms. - Implement reliable integration solutions using timeouts, retries, idempotency, resilience, and backward compatibility practices. - Troubleshoot API proxy failures, backend connectivity issues, latency, and end-to-end integration defects. - Develop unit, integration, and API tests using frameworks such as pytest. - Participate in technical design discussions, code reviews, and architectural decisions. - Implement automated testing, source control, CI/CD, and deployment best practices. - Collaborate with architects, developers, security teams, and business stakeholders to deliver reliable integration solutions. - Identify opportunities to improve developer productivity through AI-assisted engineering and contribute to engineering best practices. Bachelor’s or master’s degree in computer science, Information Technology, or a related field.