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Overview
Mid-Level

Applied AI Engineer

Confirmed live in the last 24 hours

DoiT International

DoiT International

Remote Estonia
Remote
Posted April 3, 2026

Job Description

Location
Our Applied AI Engineer will be an integral part of our global business systems team. This role is based remotely in the US East, the UK, Ireland, Estonia, the Netherlands, Sweden and Israel.

Who We Are
DoiT is a global technology company that works with cloud-driven organizations to leverage the cloud to drive business growth and innovation. We combine data, technology, and human expertise to ensure our customers operate in a well-architected and scalable state - from planning to production. 

Delivering DoiT Cloud Intelligence, the only solution that integrates advanced technology with human intelligence, we help our customers solve complex multicloud problems and drive efficiency.

With decades of multicloud experience, we have specializations in Kubernetes, GenAI, CloudOps, and more. An award-winning strategic partner of AWS, Google Cloud, and Microsoft Azure, we work along

The Opportunity
We are bringing the "Full Stack Builder" model to DoiT's internal operations. As an Applied AI Engineer, you are a one-person product team embedded directly into a core business function.

This is not an IT support role. You are not fielding tickets. You have a dedicated product surface - your assigned department - and a clear success metric: measurable process improvement, shipped fast. You will rely on your empathy and judgment to identify the friction, and you will use modern AI tooling to build, code, and deploy the automations end-to-end.

You live and breathe AI. You automate your own life for fun, you use AI agents as an extension of your own brain, and you get a genuine dopamine hit from taking a slow, manual process and turning it into a seamless, AI-driven workflow.

What We're Looking For:

  • The Solver Mindset: You can research a problem, design a solution, code it, and launch it. You use AI coding assistants heavily to multiply your own output.
  • The AI-Native Builder: You don't just know about AI. You build with it daily. You instinctively reach for tools like Claude Code, Gemini CLI and Codex to multiply your output.You are fluent in modern AI coding environments and autonomous agents like Claude Code.
  • Strong Software Fundamentals: You produce production-quality code, not just brittle scripts.
  • AI Integration Experience: Hands-on experience with LLM APIs, prompt engineering, RAG,  MCP, and agent-based architectures.
  • Extreme Empathy: Translating messy, real-world business workflows into clean technical solutions requires deep listening and communication skills. You can speak "Engineering" and business language equally well.
  • Self-Direction: There is no established playbook for this role. You will need to find the work, scope it, build it, and prove it mattered

Required Tech Stack & Skills

AI & LLM Stack

  • AI Agents: you live and work inside AI agents like Claude Code, Gemini CLI, and Codex. This is not optional and not a nice-to-have. AI-driven engineering is how we build at DoiT. You use AI agents as an extension of your brain to research, code, test, and deploy - and you can critically evaluate the output. If you're not already shipping production code through AI agents daily, this role is not for you.
  • LLM APIs: hands-on experience with the Anthropic Claude API (primary) and/or OpenAI API, Google Gemini API
  • Relentlessly Current: the AI stack moves weekly, not yearly. You follow model releases, new agent frameworks, protocol changes, and tooling updates as they happen. You don't wait for a blog post summary - you read the changelog, try the beta, and know when to adopt and when to skip. Today it's MCP and Claude Code, six months from now it might be something else entirely. You'll be the first to know.
  • MCP (Model Context Protocol): building or consuming MCP servers to connect AI agents to external tools and data sources
  • Agentic Architectures: designing multi-step agent workflows with tool use, decision-making, human-in-the-loop escalation, and guardrails
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