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Middle AI / Agent Engineer

Role overview

Qualifications

  • Hands-on experience with LLMs and prompt engineering
  • Experience building and configuring AI agents
  • Working knowledge of LLM APIs
  • Ability to write code in at least one scripting language for automation and integration tasks

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

Key facts

  • Remote from: Anywhere
  • Full time
  • AI Engineer
  • English

Hard skills

Other skills

  • Analytical Skills
  • Problem Solving
  • Detail Oriented

About the company

RichBrains logo

RichBrains

  • IT Services & Consulting
  • SME
  • 51–200
RichBrains is a custom software engineering company with an Agile mindset, deep domain expertise in EdTech, and Amazon and Salesforce partnerships under our belt. We'll guide your project from inception to a full-fledged tech solution. Key Services: • Full-cycle custom software development for web & mobile • Application migration & integration • Legacy application or database migration • AWS cloud-based solutions • Intelligent document processing • SalesForce migration & integration • Open source LMS migration & integration • UX/UI and product design • Discovery & software prototyping • MVP and SaaS development We're flexible, you don't need to start a collaboration with us from large-scale projects. Typically, we begin with a small discovery phase, when we provide product prototypes. This aligns our visions and ensures mutual comfort before upscaling. As trust builds, we gradually expand into long-lasting partnerships. Since 2006 we've been bringing digital innovations to clients across the globe, in the USA, Canada, Western Europe, and Australia. Our team possesses a versatile approach and experience with businesses of all scales. We've been successfully delivering projects for Flo, Boston University, London School of Business & Finance, TBWA France, Smartomica, Ballantines, University of Europe, and numerous other organizations.

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Job description

This is a remote position.

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 retrieval/ranking techniques;
  • Multi-agent orchestration – LangChain, LangGraph or similar;
  • No-code / low-code automation experience;
  • Experience with STT / TTS integrations;
  • Understanding of MCP and agent protocols;
  • Cloud AI deployments – Amazon Bedrock or Azure OpenAI;
  • Familiarity with monitoring and observability tools for AI system.

Benefits

  • Collaborating with a highly motivated and professional team, which values your ideas and expertise;
  • Working hours: 11:00–20:00 GMT+3;
  • Regular performance reviews;
  • Corporate discount programs;
  • Opportunities for training and certifications;
  • Team events and get-togethers to foster team spirit.

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