AI Engineer

About the role

We are looking for a hands-on AI Engineer to join a small, fast-moving startup and help build a new AI-driven product from the ground up.

The role focuses on turning product ideas into working AI features: selecting and integrating models, designing LLM-based pipelines, building prototypes and taking them to production. You will work closely with the founders and the product team, have a direct influence on the technical architecture, and see the impact of your work on real users from day one.

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Responsibilities

• Design, develop and deploy AI-powered features for a new product, from prototype to production;
• Build and optimise LLM-based solutions, including prompt engineering, RAG pipelines, agents and tool integrations;
• Select, evaluate and integrate foundation models and third-party AI APIs based on quality, cost and latency;
• Set up evaluation frameworks to measure model performance and continuously improve output quality;
• Develop backend services and APIs that connect AI components with the core product;
• Work with data: collection, cleaning, embeddings, vector databases and fine-tuning where needed;
• Collaborate closely with founders and product to define the roadmap, prioritise experiments and translate business needs into technical solutions;
• Monitor production systems, manage costs and ensure the reliability, security and scalability of AI features.

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Requirements

• 3+ years of software engineering experience, including at least 1–2 years building ML or LLM-based products;
• Strong Python skills and experience with modern AI frameworks and tooling (e.g. LangChain, LlamaIndex, Hugging Face, PyTorch);
• Hands-on experience with LLM APIs, RAG architectures, vector databases and prompt engineering;
• Solid backend skills: building APIs, working with databases and deploying services in the cloud (AWS, GCP or Azure);
• A track record of shipping AI features to production, not only research or prototypes;
• Product-minded, proactive and comfortable working in an early-stage environment with high ownership and ambiguity;
• Strong English; additional languages are an advantage;
• Experience in a startup or with MLOps, fine-tuning or multi-agent systems is a strong plus.

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