Middle AI / Agent Engineer

We're looking for a proactive Middle AI / Agent Engineer to take full ownership of AI initiatives and build and implement advanced solutions that support real business workflows. Someone who treats LLMs as engineering components, not a chat interface. You'll take an idea and turn it into something that runs in production: agents, RAG pipelines, prompt systems, integrations that solve real business problems.

No model training. Just solid, reproducible AI solutions built by a practitioner who thinks systematically and knows how to get consistent output from LLMs.

Responsibilities:

• Write, test, validate, and iteratively improve prompts and system instructions until results are stable and reproducible;

• Build and configure AI agents - tool-use, memory, multi-step workflows;

• Implement RAG pipelines and connect LLMs to external data sources and APIs;

• Write integration and automation code (Python, Node.js, or any scripting language);

• Evaluate AI output quality in a structured way - accuracy, reliability, security and cost;

• Compare models (OpenAI, Anthropic, Gemini etc) and recommend the right one for the task;

• Monitor solutions in production, catch failures, and improve performance;

• Stay current with LLM ecosystem - new models, tools, and frameworks - and apply relevant findings to your work.

Requirements:

• Hands-on experience with LLMs and prompt engineering –systematic work, not occasional ChatGPT usage;

• Experience building and configuring AI agents (planning, tool-use, memory);

• Working knowledge of LLM APIs - OpenAI, Anthropic, Google, or similar;

• Ability to write code in at least one scripting language for automation and integration tasks;

• Understanding basic AI evaluation techniques;

• Strong analytical and problem-solving mindset with attention to detail – able to explain why a solution was chosen;

• English B2+ (written and spoken).

Nice to have:

• Experience with RAG , vector databases and other…