AI Engineer

Research & Development

∙

UK, EU and Eastern Europe, Ukraine, remote

∙

April 22, 2026

Our client is a product-focused company building AI solutions for businesses that want to move from experimentation to real operational impact. They work on practical AI adoption, helping clients design and implement intelligent systems that improve workflows, automate manual processes, and create measurable business value in production environments.

They are looking for an AI Engineer who can take ownership of the full AI delivery cycle and build production-ready solutions across client engagements. In this role, you will design, develop, and ship end-to-end AI systems, including RAG pipelines, prompt engineering workflows, LLM integrations, evaluation frameworks, and observability layers that ensure quality and reliability in production. This is a highly hands-on role for someone who enjoys turning ideas and proof of concepts into scalable, maintainable solutions that work across multiple client environments. You will work closely with the Technical Delivery Lead to translate business needs into intelligent product features, while also using AI-powered development tools, agents, and modern automation workflows to move faster and expand what a small, high-performing team can deliver.

Responsibilities

AI and LLM application delivery:
- Design, build and optimise RAG pipelines including retrieval strategies, chunking, re-ranking and embedding-based search;
- Develop and refine prompts and guardrails for domain-specific LLM applications across client engagements;
- Implement hallucination detection, mitigation and fact-checking mechanisms that give clients confidence in AI outputs;
- Build intelligent features (search, recommendations, classification, summarisation) powered by LLMs and embeddings;
- Validate AI features with real users and iterate based on qualitative and quantitative feedback.
Evaluation, monitoring and reliability:
- Set up and maintain LLM evaluation frameworks to measure quality, relevance and reliability across deployed solutions;
- Implement observability and monitoring for production AI systems so problems surface before clients notice them;
- Continuously improve AI outputs based on evaluation data, usage patterns and client feedback.
Platform and system integration:
- Integrate AI capabilities into client-facing products built on Next.js, TypeScript and Supabase;
- Build and maintain backend services and API routes that connect LLM providers, vector databases and client systems;
- Work with the ARIA platform where applicable, extending and improving its AI capabilities;
- Ensure AI solutions meet client requirements for security, scalability and data governance.
AI-native development workflow:
- Use AI-powered development tools (Cursor, Claude Code or equivalent) daily to scaffold, build and iterate on AI features faster than traditional methods allow;
- Build and configure AI agents that automate repetitive development tasks: test generation, code review, documentation scaffolding and regression testing;
- Evaluate and recommend new AI development tools and frameworks, separating signal from noise for the wider team;
- Contribute to internal tooling and best practices that raise the AI engineering bar across the company.

Requirements

4+ years of professional software engineering experience, with at least 2 years focused on applied AI/ML or LLM-based systems in production;
Proficiency in TypeScript and Python;
Strong hands-on experience building and operating production AI applications, including RAG, prompt engineering and evaluation;
Experience implementing hallucination detection and mitigation techniques in real-world deployments;
Experience working with vector databases (Weaviate, Pinecone or similar) and embedding-based search;
Production experience using Claude (Anthropic) and/or OpenAI APIs;
Experience with LLM evaluation and observability tools (Langfuse, Weights and Biases or custom solutions);
Strong experience with AI-native development tools like Cursor, Claude Code or equivalent, with the ability to use AI to build AI solutions faster and more effectively;
Upper-Intermediate English, both verbal and written.

Bonus points for

Experience with Next.js and Supabase, or similar technologies;
Experience with document processing, including PDF extraction, OCR, and structured data extraction from unstructured sources;
Exposure to audio or speech processing, such as Whisper or similar tools;
Experience with ML classification, model fine-tuning, or training;
Experience building AI solutions for the Direct Selling industry;
Advanced degree in a relevant field such as Computer Science, Data Science, or AI/ML.

We offer excellent benefits, including but not limited to

People-oriented management without bureaucracy;
Flexible schedule;
Opportunities for self-realization, career, and professional growth.

AI Engineer

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AI Engineer

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