Applied AI Engineer

Role overview Build applied AI systems that bring language models into real business workflows. The work spans agent design, retrieval-augmented generation (RAG), evaluation, and production readiness, with opportunities to discuss technical choices directly with clients.

Responsibilities - Design agents by shaping prompts, connecting tools, and coordinating multi-step tasks. - Build retrieval pipelines from data ingestion through retrieval strategy. - Develop evaluation tools and regression checks to assess systems before launch. - Prepare AI applications for production with security controls, guardrails, and observability. - Lead technical discovery conversations and explain engineering trade-offs to clients.

Requirements - A degree in computer science or engineering, or equivalent professional experience. - Fluent written and spoken English. - Strong Python skills and experience working in typed, tested, reviewed codebases. - Practical experience building RAG and agent-based applications. - Experience with Docker, CI/CD, and at least one cloud platform.

Nice to have - Familiarity with model fine-tuning, distillation, or quantization. - Experience in a regulated field such as healthcare or finance. - Consulting or agency experience, or work with voice, real-time, or multimodal systems.

Benefits and work setup - Remote work with flexible hours. - Wellness perks, a collaborative team environment, and room to shape a career path.