Junior AI Engineers and err, Gemologists

Responsibilities

• You will work for a fast-growing AI company in London, writing C# .NET code that integrates language models into real-world software products.
• You will build and maintain backend services and APIs in C# (.NET) that expose AI model functionality to applications and end users.
• You will integrate pre‑trained LLMs into .NET applications via REST APIs and SDKs — including Anthropic's Claude API — working under the guidance of senior engineers.
• You will use Claude Code as an AI‑powered coding assistant in your daily workflow, accelerating development, generating boilerplate, and getting unstuck faster.
• You will write C# code to call, orchestrate, and manage AI model endpoints — including handling prompts, responses, retries, and error states.
• You will implement prompt engineering logic in C# — structuring inputs and parsing outputs to ensure responses are accurate, reliable, and safe.
• You will write unit and integration tests in C# to ensure AI‑powered features behave correctly and reliably in production, using Claude Code to help generate and review test cases.
• You will help debug unexpected model behaviour such as hallucinations and biases, using Claude Code alongside logging and monitoring tools within the .NET application stack.
• You will use Git every day for version control and get introduced to CI/CD pipelines — using Claude Code to help write, review, and improve your commits from day one.
• You will work with .NET libraries and Azure AI/OpenAI SDKs — and Anthropic's Claude SDK — to bring language model capabilities into scalable, maintainable software.
• You will collaborate with data engineers, NLP researchers, and product owners — contributing to code reviews and using Claude Code to level up your contributions from the start.
• You will document your code, integrations, and experiments clearly, with Claude Code helping you write and maintain technical documentation as you go.
• You will learn ethical AI and software engineering best practices — building systems in C# and .NET that are robust, fair, and safe for real users.