Details:
- Salary: £100,000 - 110,000 - Annum
- Job Type: Permanent
- Job Status: Full-Time
- Salary Per: Annum
- Location: North West
- Date: 20 hours ago
Description:
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