Key skills
AI coding assistantsClaude CodeGemini CLICodexModern AI coding environmentsAutonomous agentsSoftware developmentLLM APIsPrompt engineeringRetrieval-Augmented Generation (RAG)Multi-Channel Processing (MCP)Agent-based architecturesEmpathySelf-DirectionTypeScriptAILLMClaudeGeminiRAGNext.jsCloud RunCommunication
About this role
DoiT is a global technology company that helps organizations leverage the cloud for business growth and innovation. As an Applied AI Engineer, you will be responsible for automating workflows within a core business function, using modern AI tools to improve processes and train team members on new technologies.
Responsibilities:
- Audit real workflows in your assigned department. Find the "Human API" moments where smart people are doing robotic work (copy-pasting, manually reconciling data)
- Build default, pre-configured AI setups for your department teammates. Don't make an accountant figure out how to connect an LLM to NetSuite; build the integration, secure the endpoints, and hand them the keys
- Build and deploy initial AI-powered automations using DoiT's standard stack (Next.js, TypeScript, Firestore, Cloud Run, and Claude API) to build trust and show what's possible
- Train your department teammates on the tools you build. Foster their growth so they can start writing their own prompts, configuring their own agents, and automating their own workflows
- Track the time and cost savings for every automation shipped in your department. No vanity metrics, just real business outcomes
Requirements:
- 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