Senior Staff Engineer (Google Apigee Development)

Job description

👋🏼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.