openleverjobgether
Intermediate Cloud / AI Developer
Jobgether
LocationUS
EmploymentFull-time
Posted2026-08-24T11:29:28.743000+00:00
Last observed2026-08-26 21:51:40.410433
Job idjobgether-jobgether:lever:1bbcbdc5-6639-4610-bb73-576df8b8bd76
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Intermediate Cloud / AI Developer based in the United States. The Intermediate Cloud / AI Developer designs, develops, tests, and supports modern Java-based applications in a cloud-native environment. The role focuses on building secure, scalable solutions on Google Cloud Platform that improve business workflows and enable data-driven capabilities. You will develop RESTful APIs, integrate approved AI services, and contribute to reliable application architectures and deployment practices. Working closely with DevOps, QA, product, and security teams, you will help deliver solutions that meet performance, security, and compliance expectations. The position offers increasing technical independence, with opportunities to influence design decisions and contribute to architecture and engineering standards. You will also play an important role in troubleshooting, observability, CI/CD automation, and production support. This is an opportunity to grow your cloud and AI engineering expertise while working on meaningful, mission-oriented technology in a fully remote environment. Design, develop, test, maintain, and support Java-based applications using modern software engineering and cloud-native practices. Build and enhance cloud solutions on Google Cloud Platform supporting data ingestion, processing, storage, retrieval, and distribution. Develop and maintain RESTful APIs, including versioning, documentation, backward compatibility, authentication, authorization, and integration with internal and external systems. Integrate approved AI services and models into applications for use cases such as summarization, extraction, classification, and decision support. Contribute to AI evaluation and monitoring practices to help ensure application quality, reliability, and responsible use. Apply secure engineering principles, including least-privilege access, secrets management, encryption, audit logging, and policy-aligned data handling. Troubleshoot application issues independently across development, testing, and production environments, performing root-cause analysis and implementing preventative fixes. Contribute to CI/CD pipelines, deployment automation, release processes, and software delivery improvements in partnership with DevOps teams. Implement and maintain observability capabilities, including structured logging, metrics, dashboards, alerts, and operational documentation. Collaborate with engineering, QA, DevOps, product management, and security stakeholders to plan releases, support testing, and resolve production issues. Participate in architecture and technical design discussions and contribute to code reviews and engineering standards. Support continuous improvement across development practices, application reliability, performance, security, and operational processes. Provide guidance and mentorship to junior developers through knowledge sharing, code reviews, and technical example. Participate in production support activities and contribute to post-incident analysis and corrective actions when required. Requirements Bachelor’s degree in a relevant technical field from an accredited college or university; candidates without a relevant four-year degree may qualify with an additional four years of relevant experience. 3+ years of professional experience developing backend applications or services using Java. Hands-on experience with cloud services and deploying applications on Google Cloud Platform or comparable cloud environments, with the ability to quickly adapt to GCP. Experience designing and implementing RESTful APIs and working with common authentication, authorization, and integration patterns. Experience integrating AI capabilities into applications, including calling AI APIs or services for summarization, extraction, classification, or decision-support use cases. Familiarity with fundamental A
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