Freelance AI Engineer

We’re supporting a London-based product company building a data-driven platform used by investment teams in the private markets space. The product focuses on collecting, structuring, and analysing large volumes of complex and unstructured data to surface insights and support decision-making.
The company is fully bootstrapped, profitable, and operates with a small, senior, product-driven engineering team.

The Role

This is a fulltime, fully remote, B2B contract role. The engagement is intended to be longterm, with continuity and deep involvement in the evolution of the product.
The total annual compensation range for this position is €80,000–€120,000, depending on experience and seniority.

As an AI Engineer, you’ll work on the core AI capabilities of the product, with a strong focus on building, deploying, and maintaining ML and LLM-based systems in production.
This is a hands-on engineering role centred on applied AI, with real ownership of features that are directly used by customers.

What you’ll work on

• Designing, building, and deploying AI-driven features embedded in the core product
• Working with unstructured and semi-structured data to extract, enrich, and structure information
• Implementing LLM-powered and retrieval-based workflows used in production
• Integrating AI components with backend services and data platforms
• Collaborating closely with data and product teams to define and deliver AI functionality
• Maintaining, monitoring, and iterating on AI systems with a focus on reliability and scalability

Requirements (hard skills)

• Strong experience with Python, including building backend services and APIs (e.g. FastAPI or similar frameworks)
• Hands-on experience working with LLMs (e.g. OpenAI, Anthropic, or equivalents), including prompt engineering, tool usage, and RAG patterns
• Familiarity with agentic or orchestration frameworks (such as Pydantic AI, LangChain, or similar)
• Solid SQL skills, with experience designing AI features that interact with relational databases
• Some exposure to traditional machine learning models, alongside LLM-based systems
• Experience with vector databases and embedding-based retrieval approaches
• Habit of keeping up with the rapidly evolving AI landscape, with ongoing experimentation and learning
• Fluent English

Big plus

• Proven experience delivering production-grade AI features, not limited to prototypes or experiments
• TypeScript experience, enabling effective collaboration with frontend engineers

Plus

• Experience with ClickHouse or other column-oriented / analytical databases
• Familiarity with infrastructure and DevOps practices
• Previous experience working on data-intensive products