About the Role

We're looking for a curious, self-driven AI Automation / Forward Deployed Engineer to build custom AI-powered applications and automation tools for our teams and clients. This is a hands-on, build-from-scratch role — you'll work directly with LLM APIs, agent frameworks, and retrieval systems rather than off-the-shelf platforms, deploying straight into live business workflows. Fresh graduates are encouraged to apply — we value drive and problem-solving over years of experience.Key Responsibilities

• Build and maintain automation apps and AI agents from the ground up for internal teams and client engagements
• Integrate LLM APIs (Claude, OpenAI) into tools and business workflows
• Develop and tune RAG pipelines — document ingestion, chunking, embeddings, vector search, retrieval quality
• Deploy and manage AI agent environments such as OpenClaw across servers and workstations
• Connect systems via REST APIs and webhooks (messaging platforms, databases, cloud services)
• Work directly with end users and clients to understand their workflows and ship solutions that fit them
• Write and refine prompts; evaluate output quality and iterate
• Test, document, and troubleshoot deployed automations
• Research emerging AI tools and models, and recommend practical use cases

Requirements

• Bachelor's degree in IT, Computer Science, Engineering, or related field (fresh graduates welcome)
• Active user of AI tools (Claude, ChatGPT, Gemini, etc.) beyond basic conversation
• Basic understanding of REST APIs, JSON, and how systems talk to each other
• Basic coding logic — Python or JavaScript/Node.js preferred
• Comfortable working in the terminal and experimenting independently with new tools
• Strong logical thinking and problem-solving skills
• Able to explain how a system works, not just use it
• Comfortable communicating with clients and end users directly
• Organized, detail-oriented, and proactive

Nice to Have

• Familiarity with RAG concepts — embeddings, vector search, retrieval
• Experience with agent frameworks or AI coding tools
• Familiarity with GitHub, Docker, or Linux server administration
• Personal projects or portfolio involving AI or automation
• Understanding of token costs, context windows, and model selection tradeoffs