Senior RAG Engineer (Remote/Hybrid) — AI Architect

Jobsinkent; United Kingdom; Hybrid; CAD 151,000 - 226,000; Full time

Benefits offered by this job

Competitive salary and bonus

Flexible remote/hybrid working

Personal development budget

Opportunity to influence future AI方向

Job summary

Jobsinkent in the UK seeks a skilled RAG Engineer to design and build enterprise-grade AI applications powered by large language models. Work remotely or in a hybrid setup, collaborating with ML and software teams to deliver scalable AI products.

You will optimize retrieval pipelines, embeddings, and guardrails while integrating with enterprise data sources and APIs. The role demands strong Python, experience with LangChain or LlamaIndex, and a keen eye for reliability and security.

Qualifications

• Commercial experience building RAG-based AI applications.
• Strong Python development skills and experience with LLM frameworks.
• Familiarity with vector databases and embedding models.
• Experience deploying AI apps on major cloud platforms.

Responsibilities

• Design and build Retrieval-Augmented Generation architectures.
• Develop production-ready AI applications using modern LLM frameworks.
• Optimise vector search and embedding strategies.
• Build ingestion pipelines for structured and unstructured data.
• Engineer prompts, evaluation frameworks and guardrails.
• Integrate LLMs with enterprise APIs, databases and knowledge bases.
• Collaborate with ML, software and product teams to deploy at scale.

Skills

Python development

LangChain / LlamaIndex

Vector databases

Embedding models

OpenAI / Anthropic / Gemini

Prompt engineering

Cloud deployment

Communication skills

Tools

Kubernetes

Docker

Job description

Jobsinkent in the UK seeks a skilled RAG Engineer to design and build enterprise-grade AI applications powered by large language models. Work remotely or in a hybrid setup, collaborating with ML and software teams to deliver scalable AI products.

You will optimize retrieval pipelines, embeddings, and guardrails while integrating with enterprise data sources and APIs. The role demands strong Python, experience with LangChain or LlamaIndex, and a keen eye for reliability and security.