AI Platform Engineer

Portfolio Group Ltd

Manchester, UK

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Compensation

£80,000.0 - £100,000.0

Working hours

Regular working hours

Job source

www.reed.co.uk

Tech stack

Artificial Intelligence Audit Trail Microsoft Azure Software as a Service Cloud Engineering Databases Extract Transform Load (ETL) DevOps Fault Tolerance Github Identity and Access Management Python (Programming Language)

+12 more

Search Technologies Data Streaming Management of Software Versions Datadog Azure Data Factory Large Language Models Containerization AI Platforms Search Engines Api Design Terraform Microservices

Job description

Join a high growth international SaaS business as an AI Platform Engineer, where you will design, build, and operate the AI platform that underpins our clinets conversational assistant and wider AI initiatives.

You will take responsibility for the runtime, infrastructure, and operational foundations underpinning our RAG pipelines, LLM orchestration, and vector search, built across Microsoft Azure and Microsoft Foundry. Where prototypes and proof-of-concepts exist, you will be the one turning them into resilient, production-ready services, working alongside AI Engineering, DevOps, and Info-Sec to get them there.

What You’ll Do

Build and extend a scalable AI platform via Microsoft Foundry.
Own and optimise Foundry solutions for accuracy, scale, and latency.
Harden the production RAG pipeline, covering inference, retrieval, and ingestion.
Architect Azure services using Terraform infrastructure-as-code.
Scale vector database and embedding pipelines.
Build end-to-end observability across latency, throughput, cost, and system health.
Strengthen resilience through fault-tolerance, caching, and autoscaling.
Maintain CI/CD pipelines through GitHub and Azure DevOps.
Automate embedding generation and knowledge base synchronisation.
Embed secure-by-design principles, including IAM, encryption, and safe data flows.
Mature governance practices, including versioning, audit logging, and compliance.

Requirements

Proven enterprise delivery on Microsoft Azure.
Azure Data Factory experience for ETL workflows.
Familiarity with vector databases or search engines such as OpenSearch.
Strong Python skills.
Experience with containerisation and Terraform.
Solid grasp of microservices, API design, and cloud-native architecture.
Observability tooling experience, such as OpenTelemetry, is a plus.
Background in platform or infrastructure engineering within production environments.
Track record owning cloud platforms with accountability for reliability and scale.
Experience with production AI-enabled platforms is an advantage.
Autonomous, ownership-driven approach with a strong focus on reliability.