Full Stack AI Engineer

Full Stack AI Engineer Remote (UK) | Up to 95k

A fast-growing, venture-backed tech company is seeking a Full Stack AI Engineer to join its mission to revolutionise the market sector they are in. This is a hands-on opportunity to help shape the technical vision of a cutting-edge AI platform from the ground up.

Youll be part of a collaborative development team solving real-world problems, building scalable solutions from prototype to production, and contributing directly to the companys growth milestones.

Key Responsibilities

• Backend APIs (Python/FastAPI) : Build secure, scalable services powering AI features and data retrieval.
• RAG & Vector Search : Design and iterate retrieval pipelines using chunking, embeddings, hybrid search, and feedback loops.
• LLM Integration : Work with OpenAI/Bedrock models, orchestrate prompts/responses, and implement guardrails and evaluations.
• Data Engineering : Ingest and transform structured/unstructured data; design schemas for analytics and retrieval.
• Frontend (React/Next.js) : Deliver fast, intuitive UIs that clearly expose AI capabilities.
• Architecture : Develop a modular platform on AWS ECS, separating ingestion, retrieval, reasoning, and delivery.
• Quality & Reliability : Implement testing, CI/CD, observability, and performance tuning.
• Collaboration : Partner with Product and leadership; mentor engineers; contribute to technical strategy.
• Innovation : Explore and recommend new tools and frameworks for full-stack and AI development.

Experience:

• 5+ years of full-stack development experience.
• Strong proficiency in Python (FastAPI) and React/Next.js.
• Experience with RAG systems, vector databases (pgvector, FAISS, Weaviate), and hybrid search.
• Deep understanding of chunking, indexing, reranking, and evaluation metrics.
• Solid experience with SQL and NoSQL databases (Postgres, DynamoDB).
• Familiarity with AI/ML models and APIs (LLMs, embeddings, vector search).
• Expertise in data engineering (ETL, schema design, performance tuning).
• Proficiency in AWS and containerized deployments (Docker, ECS).
• Strong grasp of secure coding practices and data handling.
• Excellent communication, problem-solving, and leadership skills.