Applied AI Engineer
New
D
DoiTCloud Technology
Remote EMEA, this role is based remotely in Eastern Europe or Indonesia.Full-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- Typically 3-9 years of professional software engineering experience.
- Required Skills
- PythonGCPOAuthTypeScriptGoReactRESTful APIs
Requirements
- End-to-end product delivery: experience shipping and operating production software with real users.
- Backend engineering: proficient in Python or Go, with the ability to design and deploy services to Cloud Run.
- Frontend engineering: proficient in TypeScript and React for building dashboards or admin tools.
- Cloud infrastructure: experience deploying and operating on GCP with knowledge of IAM, secrets management, and deployment pipelines.
- API and systems integration: experience connecting multiple third-party platforms in production including REST APIs, webhooks, OAuth, and event-driven patterns.
- Security baseline: strict adherence to secrets management, avoiding hardcoded credentials, and ensuring no PII in logs.
- AI-assisted development: active use of AI tooling (e.g., Claude Code) across the SDLC with the ability to critically review AI output for correctness and security.
- Typically 3-9 years of professional software engineering experience.
Responsibilities
- Own internal tools end to end - from understanding the operational problem through design, implementation, deployment, and iteration.
- Build across the stack as the product requires: Python/Go services on Cloud Run, TypeScript web apps and internal admin tools, event-driven integrations on Pub/Sub, and cloud infrastructure on GCP.
- Integrate with third-party SaaS platforms and cloud APIs - handling REST, webhooks, OAuth, and event-driven patterns, including failures, retries, and schema drift.
- Build and maintain workflow automation and business process orchestration as named, observable flows rather than logic buried in vendor scripts.
- Use AI tooling effectively across the development lifecycle - spec, code, and review - directing Claude as a coding collaborator while owning the output.
- Review AI-generated code before it ships for correctness, security, and type safety.
- Operate what you ship: monitoring, reliability, cost, and failure modes in production.
- Contribute to shared engineering standards, playbooks, and internal tooling.
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