Applied AI Engineer: Enterprise AI & Knowledge Graph

IFS; Greater London; Hybrid; GBP 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Flexible remote/hybrid working

Zusammenfassung

IFS is building AI-native enterprise software and seeks engineers who can design, build and ship production AI applications at scale. The role focuses on creating semantic layers, knowledge graphs, and grounding infrastructures to enable intelligent agents across the product ecosystem.

You will work with LLMs, retrieval-augmented generation, and orchestration frameworks in a cloud-native environment. The team emphasizes hands-on delivery, system reliability, observability, and collaboration with

Qualifikationen

• Strong software engineering foundation with production experience in enterprise systems.
• Experience delivering AI systems built on large language models and RAG.
• Hands-on design and operation of cloud-native architectures and APIs.
• Deep knowledge graphs, ontologies, and semantic modelling for enterprise data.
• Experience with agent frameworks and multi-agent orchestration.

Aufgaben

• Design and build MCP servers and capability modelling for agent access to product data.
• Create a semantic layer consisting of ontology and knowledge graph for the platform.
• Develop retrieval, grounding, embeddings, and vector database strategies for agents.
• Establish data quality, provenance and versioning for the knowledge graph.
• Build the control plane, authentication, entitlements and security for agents.

Ausbildung

Bachelor's degree in Computer Science

Tools

Docker

Kubernetes

Azure/AWS/GCP

Semantic Kernel/OpenAI Agents SDK

Jobbeschreibung

IFS is building AI-native enterprise software and seeks engineers who can design, build and ship production AI applications at scale. The role focuses on creating semantic layers, knowledge graphs, and grounding infrastructures to enable intelligent agents across the product ecosystem.

You will work with LLMs, retrieval-augmented generation, and orchestration frameworks in a cloud-native environment. The team emphasizes hands-on delivery, system reliability, observability, and collaboration with