Applied AI Engineer

We are looking for an Applied AI Engineer to build production-grade LLM and VLM-powered features, owning the AI logic and backend systems from concept to production.

✅ Your responsibilities:

• Design, develop, and deploy AI-powered product features using LLMs and multimodal models

• Build and maintain backend services supporting AI applications and workflows

• Develop evaluation frameworks, golden datasets, and automated quality measurement pipelines

• Design and implement multi-step agent workflows with tool usage, memory, error recovery, and human-in-the-loop processes

• Build scalable APIs and backend components supporting AI services

• Improve model reliability, performance, and response quality in production environments

• Implement engineering best practices including testing, monitoring, rate limiting, retry mechanisms, and fault tolerance

• Collaborate with cross-functional teams to deliver end-to-end AI solutions

🧠 Our requirements:

• Commercial experience building and shipping production LLM applications

• Experience designing and implementing AI evaluation frameworks

• Practical experience with LLM-as-a-Judge, golden datasets, or regression testing approaches

• Experience building agentic AI workflows and tool-using agents

• Strong software engineering fundamentals and backend development experience

• Experience with Python and/or TypeScript

• Experience designing APIs and scalable backend services

• Knowledge of prompt engineering and prompt lifecycle management

• Understanding of defensive engineering patterns such as rate limiting, idempotency, and backoff strategies

⭐ Nice to have:

• Experience with LangChain or similar orchestration frameworks

• Experience with Retrieval-Augmented Generation (RAG)

• Experience with vector databases and semantic search

• Experience with Vision-Language Models (VLMs)

• Experience building multimodal AI systems

• Experience creating automated evaluation dashboards and monitoring solutions

🌟 What we offer:

• 100% remote work.

• Opportunity to work on production AI systems used by real users

• Private healthcare

• Multisport

• Life insurance

• High ownership and end-to-end responsibility for delivered solutions

• Exposure to modern LLM, multimodal, and agent-based architectures

• Ability to influence product direction and technical decisions

• Collaboration with experienced engineers building AI-driven products