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