AI Engineer
Salary: £65,000 £80,000
Location: Fully remote
We are seeking an AI Engineer with a strong open-source software background to join a fast-growing scale-up. They offer fully remote employment and have a team of engineers dedicated to developing AI-powered search and Retrieval-Augmented Generation (RAG) pipelines within DataStax-based architecture.
This role is perfect for someone with expertise in Open-source, API development, fine-tuning LLMs, and integrating AI into scalable applications. If you thrive in an AI-driven development environment, enjoy working on cutting-edge retrieval models, and have a passion for optimizing LLM performance, we want to hear from you.
Key Responsibilities:
- Develop and maintain scalable RESTful & GraphQL APIs to interact with LLMs and AI-powered search systems.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines using open-source tools like LangChain, Langflow, and DataStax Vector Search.
- Fine-tune LLMs (Hugging Face, OpenAI, Cohere, or similar) to improve response quality and domain-specific performance.
- Optimize embedding models for better semantic search and document retrieval.
- Integrate AI-driven solutions with vector databases such as DataStax Astra DB, Weaviate, or FAISS.
- Implement secure API authentication (OAuth2, JWT) and manage access controls.
- Collaborate with AI/ML, data engineering, and DevOps teams to ensure seamless system integration.
- Monitor API performance and AI search efficiency, implementing optimizations where necessary.
- Stay up to date with advancements in LLM fine-tuning, RAG methodologies, and vector search techniques.
Essential Skills & Experience:
- Programming: Strong proficiency in Opensource.
- API Development: Experience with FastAPI, Flask (Python) OR Express.js for microservices.
- RAG Development: Hands-on experience building retrieval-augmented AI search solutions.
- LLM Fine-Tuning: Experience fine-tuning models for domain-specific performance and optimizing inference speed.
- Vector Search: Knowledge of DataStax Vector Search, Pinecone, FAISS, or Weaviate.
- Deployment: Familiarity with Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Jenkins, or similar).
- Security & Authentication: Strong understanding of OAuth2, JWT, and API security best practices.
- Passionate about AI and Open Source: Demonstrated involvement in open-source projects and a passion for AI and its applications.
