Applied AI Engineer -Ukraine(Remote)

DoiT is a global technology company specializing in cloud-driven solutions, delivering the DoiT Cloud Intelligence platform. The role is part of the Business Systems Engineering division, within the Fusion platform engineering team, focused on building the internal platform that supports the company’s operations. The company serves over 4,000 customers worldwide and partners with major cloud providers such as AWS, Google Cloud, and Microsoft Azure.

• 3-9 years of professional software engineering experience with end-to-end product delivery including production operation.
• Proficiency in backend engineering with Python and/or Go, owning services through design and deployment on Cloud Run.
• Proficiency in frontend engineering with TypeScript and React for building UI components.
• Experience deploying and operating on GCP with understanding of IAM, secrets management, deployment pipelines.
• Experience integrating multiple third-party platforms in production, handling REST APIs, webhooks, OAuth, event-driven patterns including retries and schema drift.
• Security best practices: no hardcoded credentials, use of secrets management tools (SOPS, Secret Manager or equivalent), no PII in logs, solid application security hygiene.
• Active use of AI tooling in the full SDLC, reviewing AI outputs critically for correctness, security, and type safety, and directing AI for implementation tasks.

Nice to have:

• Experience with workflow automation platforms like n8n, Zapier.
• Experience with business process orchestration tools like Camunda, Temporal, or similar BPMN engines.
• Systems-level programming knowledge including async runtimes, IPC, and protocol clients.
• Knowledge of graph algorithms or graph databases such as Neo4j, Cypher.
• Experience with Rust and Tauri for desktop application development.
• Experience with infrastructure as code using Terraform.
• Experience integrating LLM APIs, prompt design, and AI safety or compliance.

• Own internal tools end to end, from problem understanding through design, implementation, deployment, and iteration.
• Build backend services in Python and Go on GCP Cloud Run.
• Develop frontend tools using TypeScript and React.
• Integrate with third-party SaaS platforms using REST APIs, webhooks, OAuth, and event-driven patterns with failure handling.
• Build and maintain workflow automation and business process orchestration using BPMN flows.
• Use AI tooling (Claude Code or equivalent) actively across the development lifecycle for specification, coding, and review.
• Review AI-generated code for correctness, security, and type safety.
• Operate production services focusing on monitoring, reliability, cost, and failure modes.
• Contribute to shared engineering standards, playbooks, and tooling.