AI Platform Engineer

AI Platform Engineer
LLMs RAG Python Cloud Infrastructure
Manchester City Centre - 5 days a week onsite
Up to £100,000 DOE

The Opportunity

We're looking for an AI Platform Engineer to build, optimise and maintain the infrastructure behind a growing portfolio of AI-powered applications.
You'll focus on developing scalable, reliable services supporting large language models (LLMs), retrieval-augmented generation (RAG), intelligent search and conversational AI. You'll take ownership of existing solutions while helping bring new AI capabilities into production.

Key Responsibilities

• Design, build and optimise production-grade AI platforms, RAG pipelines and LLM integrations.
• Develop scalable cloud-native services and backend infrastructure using Microsoft Azure.
• Improve the performance, reliability and latency of AI applications and retrieval workflows.
• Manage infrastructure-as-code using Terraform and support containerised deployments.
• Build CI/CD pipelines and automate data ingestion, embedding generation and vector indexing.
• Implement monitoring, logging, tracing and performance optimisation across AI workloads.
• Apply security, access controls, versioning and governance best practices.
• Collaborate with AI, software engineering, DevOps and security teams to deliver production-ready solutions.

Skills & Experience

• Strong Python development skills.
• Commercial experience delivering solutions using Microsoft Azure.
• Experience with data integration and ETL pipelines, such as Azure Data Factory.
• Familiarity with vector databases or search technologies, such as OpenSearch.
• Experience with Terraform, infrastructure-as-code and containerised applications.
• Understanding of APIs, microservices and cloud-native architecture.
• Experience supporting production systems, with a focus on scalability, reliability and performance.

Desirable Experience

• Building or supporting production AI applications using LLMs and RAG.
• Experience with embedding models, vector search and LLM orchestration.
• Familiarity with observability tooling such as OpenTelemetry.
• Experience taking AI prototypes and proof-of-concepts into production.

The Ideal Candidate

A proactive engineer with a strong sense of ownership, excellent problem-solving skills and the ability to turn emerging AI capabilities into reliable, scalable production services.

Sponsorship is not available.