Applied AI Engineer - Ukraine (Remote)

Job Summary

DoiT International is a global technology company that partners with cloud-driven organizations to leverage the cloud for business growth and innovation. Combining data, technology, and human expertise, DoiT ensures customers operate in a well-architected and scalable state from planning to production. As an Applied AI Engineer, you will join the Fusion team within the Business Systems Engineering division, building a composable, event-driven platform that unifies dozens of SaaS platforms across CRM, ERP, support, marketing, and billing. This role is fully remote and based in Eastern Europe or Indonesia. You will own internal tools end to end, building across a modern stack including Python, Go, TypeScript, React, GCP Cloud Run, Pub/Sub, and BPMN orchestration. AI is integral to the development lifecycle, with Claude Code used across spec, build, and review, allowing you to focus on design and judgment rather than boilerplate. The platform is built so that AI agents can operate it safely, but engineering quality, correctness, and ownership remain firmly with you. This is a high-ownership role for builders who want real distributed-systems problems and to see their work impact the business within weeks.

Key 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.

Role Requirements & Qualifications

• Typically 3-9 years of professional software engineering experience. Experience is a signal, not a gate; we care more about what you have shipped and how you think.
• End-to-end product delivery: you have shipped and operated production software with real users, not just features in isolation, but complete products from brief to deployment.
• Backend engineering: proficient in Python or Go (or both); you can own a service from design to Cloud Run deployment.
• Frontend engineering: proficient in TypeScript and React; comfortable building UI-complete features such as internal dashboards or admin tools.
• Cloud infrastructure: you deploy and operate on GCP and understand IAM, secrets management, Cloud Run, and deployment pipelines.
• API and systems integration: you have connected multiple third-party platforms in production, including REST APIs, webhooks, OAuth flows, and event-driven patterns, and know how to handle failures, retries, and schema drift.
• Security baseline: no hardcoded credentials; you use secrets management (SOPS, Secret Manager, or equivalent); no PII in logs; solid AppSec hygiene.
• AI in the development lifecycle: you use AI tooling (Claude Code or equivalent) actively across the full SDLC, review AI-generated output critically for correctness, security, and type safety, and can direct AI on multi-step implementation tasks while owning the result.

Skills Inventory

• Python or Go backend development
• TypeScript and React frontend development
• Google Cloud Platform (GCP) infrastructure management (IAM, Cloud Run, secrets management, deployment pipelines)
• API and systems integration (REST, webhooks, OAuth, event-driven patterns)
• AI tooling proficiency (Claude Code or equivalent) across the software development lifecycle
• Workflow automation platforms (n8n, Zapier, or similar) (preferred)
• Business process orchestration (Camunda, Temporal, or similar BPMN/workflow engines) (preferred)
• Systems-level programming: async runtimes, IPC, process lifecycle, protocol clients (preferred)
• Graph algorithms (cycle detection, topological sort) or graph databases (Neo4j, Cypher) (preferred)
• Rust or Tauri for desktop application development (preferred)
• Infrastructure as code with Terraform (preferred)
• LLM API integration: building features that call LLM APIs, prompt design, tool use (preferred)
• AI safety and compliance: data boundaries, output risk, regulatory awareness (preferred)

Salary & Compensation Estimation

DoiT International offers competitive compensation tailored to the Eastern Europe or Indonesia remote market. For an Applied AI Engineer with 3-9 years of experience, the expected total compensation (base salary plus benefits) ranges from approximately 50,000 to 90,000 USD annually, depending on location, experience, and skills. The role includes a comprehensive benefits package: unlimited PTO, flexible working options, health insurance, parental leave, employee stock option plan, home office allowance, professional development stipend, and peer recognition program. Benefits may vary slightly by region.