[What the role is]
We are seeking an AI Engineer to drive the design, development and operationalisation of AI-powered capabilities within the FX Platform ecosystem.
You will work across Facilities Management, Smart District and enterprise applications to develop intelligent search, conversational assistants, document intelligence and workflow automation solutions. The role combines modern AI engineering practices with cloud-native development to deliver secure, scalable and business-ready AI services.
You will work closely with product managers, service designers, software engineers and business stakeholders to transform operational knowledge and data into practical AI-enabled experiences.
[What you will be working on]
AI Solution Development
- 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.
Enterprise Search & Knowledge Management
- 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.
Intelligent Document Processing
- 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.
AI Platform Integration
- 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.
Data & Prompt Engineering
- 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.
AI Governance, Security & Responsible AI
- 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.
Cloud Engineering & MLOps
- 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.
[What we are looking for]
AI Engineering
- 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
Microsoft AI Stack
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
Software Engineering
- Proficiency in Python.
- Experience with APIs and microservices.
- Strong understanding of software engineering principles and cloud-native application development.
Data Engineering
Experience working with:
- Structured and unstructured data
- Document repositories
- Data pipelines
- Metadata and indexing strategies
Cloud & DevOps
Experience with:
- Microsoft Azure
- Docker
- Kubernetes
- GitLab
- CI/CD pipelines
Preferred Qualifications
- 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.