Apigee Integration Architect--F2F Mandate

• Design and implement scalable API and integration architectures using Apigee and modern cloud technologies.
• Lead the architecture, development, deployment, and lifecycle management of enterprise APIs.
• Develop and support integration services using Java and Spring Boot.
• Design and implement RESTful APIs and microservices following enterprise architecture and security standards.
• Configure and manage Apigee API proxies, policies, shared flows, API products, developer applications, and environments.
• Implement API security, authentication, authorization, traffic management, rate limiting, quotas, and monitoring.
• Design event-driven integrations using Apache Kafka, including producers, consumers, topics, and messaging patterns.
• Integrate enterprise applications and services across AWS cloud environments.
• Work with development and DevOps teams to establish effective CI/CD pipelines for API and integration deployments.
• Support integration with Snowflake and enterprise data platforms.
• Troubleshoot complex API, integration, application, cloud, and performance issues.
• Establish API governance, standards, reusable integration patterns, and best practices.
• Participate in architecture reviews, technical design sessions, and solution discussions with engineering and business teams.
• Collaborate with security, infrastructure, cloud, data, and application teams to deliver reliable integration solutions.
• Evaluate emerging technologies and identify opportunities to incorporate AI/LLM capabilities into enterprise integration platforms.
• Explore and support emerging Model Context Protocol (MCP) server patterns and AI-agent integration architectures.
• Ensure APIs and integrations meet enterprise security, scalability, availability, and performance requirements.
• Provide technical leadership and mentorship to development and integration engineering teams., * AWS API Gateway
• AWS Bedrock
• Docker / Kubernetes
• OpenShift
• Git / GitHub / GitLab
• Jenkins / GitHub Actions
• Terraform / Infrastructure as Code
• OAuth 2.0 / OIDC
• GraphQL
• PostgreSQL
• Microservices Architecture
• Event-driven Architecture
• API Security and Governance
• Observability / Monitoring

Leadership & Collaboration

The successful candidate will work closely with:

• Enterprise and Solution Architects
• Application Development Teams
• Cloud and DevOps Teams
• Security and IAM Teams
• Data Engineering Teams
• Infrastructure and Networking Teams

The ideal candidate will have strong hands-on experience with Apigee, Java, Spring Boot, Kafka, AWS, API Management, and enterprise integration architectures, along with practical knowledge of Snowflake, CI/CD, and emerging AI/LLM and MCP server patterns.

The candidate should be comfortable working across application development, API management, cloud, integration, data, and emerging AI technologies while providing technical architecture and hands-on engineering guidance., * 14+ years of experience in software engineering, integration architecture, API architecture, or related roles.

• Strong hands-on experience with Apigee API Management.
• Strong Java development experience.
• Strong experience with Spring Boot and Spring-based microservices.
• Hands-on experience designing and developing REST APIs.
• Strong experience with Apache Kafka and event-driven architecture.
• Strong AWS Cloud experience.
• Experience with enterprise API Management and Integration Architecture.
• Strong understanding of API security, authentication, authorization, OAuth 2.0, and related security patterns.
• Experience with CI/CD and DevOps practices.
• Practical experience with Snowflake or modern cloud data platforms.
• Strong understanding of microservices and cloud-native architectures.
• Excellent architecture, troubleshooting, communication, and stakeholder-management skills.

AI / Emerging Technology Experience

• Practical understanding of Generative AI and LLM-based architectures.
• Understanding of integrating APIs and enterprise applications with LLM/AI services.
• Familiarity with Model Context Protocol (MCP) and MCP server concepts.
• Understanding of AI-agent/API integration patterns is highly desirable.
• Experience with AWS AI/ML services is a plus.