Assistant / Manager (AI Engineer, FM Digital Platform)

• Design, develop and deploy AI-enabled solutions that improve operational efficiency and user experience.
• Build intelligent assistants, copilots and conversational interfaces for operational workflows.
• Develop Retrieval-Augmented Generation (RAG) solutions to support enterprise knowledge retrieval and question answering.
• Implement AI-powered recommendations, summarisation and insights generation capabilities.
• Evaluate and integrate emerging AI technologies into the FX ecosystem.

• Design and implement AI-powered enterprise search capabilities across applications, documents and operational knowledge repositories.
• Develop retrieval pipelines that surface relevant knowledge, documents and operational context.
• Improve search relevance, ranking and information discovery experiences.
• Support knowledge ingestion, indexing and metadata enrichment processes.
• Work on the continued evolution of AskJess and related AI-powered knowledge services.

• Develop solutions for document classification, extraction and validation.
• Build AI-assisted verification and review workflows.
• Implement automated document categorisation and tagging processes.
• Support document-centric business workflows through AI-enabled automation.

• Integrate AI services with applications across the FX Platform ecosystem.
• Expose AI capabilities through APIs and reusable services.
• Work closely with software engineers to embed AI capabilities within operational applications.
• Support integration with workflow systems, business applications and enterprise data sources.

• Design and optimise prompts, retrieval strategies and orchestration patterns.
• Develop evaluation frameworks to measure AI response quality and accuracy.
• Build data preparation and enrichment pipelines supporting AI use cases.
• Implement vector search and semantic retrieval approaches.

• Ensure AI solutions comply with organisational security, governance and data classification requirements.
• Implement responsible AI practices including transparency, explainability and human oversight.
• Monitor model performance, reliability and operational risks.
• Support auditing, evaluation and continuous improvement of deployed AI services.

• Deploy and operate AI workloads on Microsoft Azure.
• Build CI/CD pipelines supporting AI development and release processes.
• Monitor and optimise AI service performance and operational costs.
• Contribute to AI platform operational readiness and reliability.

• Experience developing enterprise AI solutions using modern LLM frameworks and AI services.
• Strong understanding of:
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Semantic Search
  • AI Agents
  • Vector Databases
  • Knowledge Retrieval Systems

Experience with one or more of:

• Azure OpenAI Service
• Azure AI Search
• Azure AI Foundry
• Azure AI Document Intelligence
• Azure AI Language Services
• Azure Machine Learning

• Proficiency in Python.
• Experience with APIs and microservices.
• Strong understanding of software engineering principles and cloud-native application development.

Experience working with:

• Structured and unstructured data
• Document repositories
• Data pipelines
• Metadata and indexing strategies

Experience with:

• Microsoft Azure
• Docker
• Kubernetes
• GitLab
• CI/CD pipelines

• Experience building enterprise search solutions.
• Experience implementing AI assistants or copilots.
• Experience with knowledge management platforms and document repositories.
• Experience supporting government or enterprise digital transformation programmes.
• Familiarity with facilities management, operational systems or smart estate technologies.