Associate Principal Engineer (Google Apigee Development)

Requirements Experience : 9+ years Strong hands-on experience in Google Apigee API development, API management, API proxy development, 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. Strong understanding of API security, authentication, authorization, access control, and enterprise integration patterns. Experience designing, developing, and managing RESTful APIs and integration services. Good understanding of OAuth 2.0, JWT, API keys, traffic management, rate limiting, quotas, caching, and API governance. Experience with Python frameworks such as FastAPI, Flask, or Django. Strong understanding of REST, HTTP protocols, JSON/XML payloads, synchronous and asynchronous integration patterns, retries, timeouts, and error handling. Ability to independently troubleshoot complex technical issues across API gateways, backend services, and multiple integration layers. Experience with Git, CI/CD pipelines, automated testing, and software development best practices. Ability to assess and validate AI-generated code for quality, security, performance, and maintainability. Strong analytical, problem-solving, communication, and collaboration skills. Ability to work independently, make sound technical decisions, and deliver solutions in an enterprise environment. Good understanding of software engineering fundamentals rather than relying solely on AI-generated code. Familiarity with Apigee X or Apigee Hybrid, Google Cloud Platform (GCP), and cloud-native application development would be an advantage. Exposure to Docker, Kubernetes, microservices, and containerized application development would be beneficial. Familiarity with MCP (Model Context Protocol), tool calling, and agentic AI development workflows would be an advantage. Experience integrating AI coding agents into enterprise development environments with appropriate security and governance controls would be beneficial. Exposure to automated security scanning, API observability, performance testing, GitHub Actions, or Jenkins would be an added advantage. Responsibilities Design, develop, deploy, and maintain enterprise APIs using Google Apigee. Develop and manage Apigee API proxies, shared flows, policies, reusable integration components, and backend integrations. 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, testing, 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 compliance with engineering standards. Integrate AI-assisted development practices into software 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 relia