Full Stack AI Engineer Location: UK remote Type: Full-time About us We are on a mission to transform how deals get done. Already trusted by leading industry organisations and fuelled by a £1.7m pre-seed raise, were building the AI platform of choice for modern dealmakers. Were a fast-growing start-up where ideas move quickly from concept to product. Our technology spans backend, frontend, data, and AI, giving our team real scope to shape the future of the product and the company itself. If youre excited by solving complex problems end-to-end, working in a collaborative environment, and having a tangible impact, youll feel at home here. The role

As a Full Stack AI Engineer, you will work within the development team to help shape the technical vision. This is a hands-on role that requires deep technical expertise, entrepreneurial drive, and the ability to create a scalable solution, from prototype to production. Youll have the opportunity to build the product from the early stages, solving real customer problems, and playing a key role in the companys journey towards achieving its business milestones. Responsibilities (including but not limited to):

Backend APIs (Python/FastAPI):

Build reliable, secure services that power AI features and data retrieval at scale. RAG & vector search:

Design, implement and iterate retrieval pipelines (chunking, embeddings, hybrid search, ranking, feedback loops). Own pgvector/Vector DB schemas, latency, relevance and cost. LLM integration:

Integrate OpenAI/Bedrock models, prompt/response orchestration, tool use, guardrails, and evaluation. Data pipelines:

Ingest and transform structured/unstructured data; design efficient schemas (Postgres/NoSQL) to support retrieval and analytics. Frontend (React/Next.js):

Ship fast, accessible UIs that expose AI features clearly (search, filters, explanations, citations). Architecture:

Evolve a modular, scalable platform (ECS on AWS), with clear boundaries between ingestion, retrieval, reasoning and delivery. Quality & reliability:

Testing (unit/integration/evals), CI/CD, observability (tracing/metrics for LLM and retrieval paths), and performance tuning. Collaboration:

Work closely with Product and ELT; mentor engineers; contribute to technical strategy and research. Innovation:

Research and recommend new tools, frameworks, and approaches for full-stack and AI development. Were looking for

A passionate individual thats hardworking and dedicated, with an entrepreneurial/ownership mindset, strong communication skills and a team player 5+ years of professional experience in full-stack development. Hands-on experience with

RAG systems ,

vector databases

(pgvector/FAISS/Weaviate/ES k-NN),

embeddings , and

hybrid search

(BM25 + vectors). Strong grasp of

chunking strategies , metadata, indexing, recall/precision trade-offs, reranking, and

evaluation

(ground-truth sets, offline/online metrics). Strong proficiency in

Python

(FastAPI) and

React/Next.js . Solid experience with

SQL and NoSQL databases

(e.g., Postgres, DynamoDB). Experience working with

AI/ML models and APIs

(LLMs, embeddings, vector search). Strong understanding of

data engineering practices

(ETL, schema design, performance tuning). Proficiency in

cloud environments

(AWS preferred) and containerised deployments (Docker, ECS). Strong grasp of

secure coding practices

and handling of sensitive data. Excellent communication, problem-solving, and leadership skills. Nice to have

Rerankers (e.g., cross-encoders), structured retrieval over SQL + vectors, query rewriting/expansion, or lightweight knowledge graphs. LLM/evals tooling (LangChain/LlamaIndex/OpenAI Evals) and feature telemetry for relevance/latency/cost dashboards. Experience in B2B data products or fintech. Get in touch!

If this role excites you and you believe youre a strong fit, wed love to hear from you. Please submit a short cover note along with your CV.

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