AI Engineer
About the Role
As an AI Engineer, you build the AI applications that organisations actually put into production — not proof-of-concepts that gather dust, but working systems that move the needle. From your base in Amsterdam, you design and ship LLM-powered solutions: retrieval-augmented generation pipelines, AI agents, internal copilots, and evaluation frameworks that keep models honest. You work hands-on with Python, Azure OpenAI or AWS Bedrock, vector databases, and modern MLOps tooling, and you treat prompts and pipelines with the same rigour as any other piece of production code.
Beyond the build, you are a sparring partner for product owners, data engineers, and business stakeholders — translating what's technically possible into outcomes that make commercial sense, and pushing back where the easy answer isn't the right one. Your future employer is an AI-first consultancy with a tight, senior team that has shipped real applications at enterprise clients across finance, healthcare, and the public sector. The culture is curious, opinionated, and pragmatic — they care about results, not hype.
Knowledge sharing happens weekly through internal tech sessions, and there's a serious budget for conferences, certifications, and experimentation time. The organisation is flat, decisions are made fast, and you have room to shape both the work and the way it's delivered.
- 3+ years building AI or machine learning applications, with at least one year shipping LLM-based systems to production
- Strong Python skills, including modern tooling (FastAPI, async, type hints, testing)
- Hands-on experience with at least one major LLM provider — Azure OpenAI, AWS Bedrock, Anthropic, or OpenAI direct
- Working knowledge of RAG architectures: embeddings, vector databases (pgvector, Pinecone, Weaviate), chunking and retrieval strategies
- MLOps fundamentals — CI/CD for models and prompts, evaluation frameworks, observability, cost monitoring
About Mellow & Jane
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