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Full stack ai engineer

Bath
Lorien Resourcing
Ai engineer
Posted: 4h ago
Offer description

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.


You’ll be part of a collaborative development team solving real-world problems, building scalable solutions from prototype to production, and contributing directly to the company’s 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.

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