Senior Apigee API & Integration Architect

Keylent Inc

Reading (Berks County)

On-site

USD 150,000 - 210,000

Full time

6 days ago
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Job summary

Keylent Inc is seeking an Apigee Integration Architect to design, develop, and support enterprise API and integration solutions in Reading, PA. The role requires hands-on expertise with Apigee, Java, Spring Boot, Kafka, AWS, and modern API management practices.

The candidate should handle API security, CI/CD pipelines, Snowflake, and AI/LLM integration patterns while guiding architecture decisions across development and DevOps teams.

Qualifications

  • 14+ years of software engineering or integration architecture experience.
  • Strong hands-on experience with Apigee API Management.
  • Strong Java development experience with Spring Boot and microservices.
  • Experience designing REST APIs and event-driven architectures.
  • Deep knowledge of API security, OAuth 2.0, and related patterns.
  • Experience with CI/CD and DevOps practices.

Responsibilities

  • Design and implement scalable API and integration architectures using Apigee and cloud technologies.
  • Lead API lifecycle management, deployment, and governance.
  • Develop and support integration services using Java and Spring Boot.
  • Design RESTful APIs and microservices following security standards.
  • Configure Apigee proxies, policies, and environments; manage API products and developer portals.
  • Collaborate with security, cloud, data, and DevOps teams to deliver reliable integrations.

Skills

Apigee API Management
Java
Spring Boot
Apache Kafka
AWS
CI/CD
Snowflake
AI/LLM
MCP server patterns
OAuth 2.0

Tools

Docker
Kubernetes
OpenShift
Git
Terraform

Job description

Keylent Inc is seeking an Apigee Integration Architect to design, develop, and support enterprise API and integration solutions in Reading, PA. The role requires hands-on expertise with Apigee, Java, Spring Boot, Kafka, AWS, and modern API management practices.

The candidate should handle API security, CI/CD pipelines, Snowflake, and AI/LLM integration patterns while guiding architecture decisions across development and DevOps teams.

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