JCDecaux UK
AIEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Engineer at JCDecaux UK. Skills: AI copilots, agentic AI, Python, ML/LLM frameworks, MLOps, Cloud platforms (Azure), LLMs, prompt engineering, RAG. Design and implement AI copilots and agentic AI solutions. Translate business use cases into Copilot scenarios”
What You'll Achieve.
augment users; automate complex workflows; enhance client and consumer understanding
Industry & Context.
automate complex workflows; optimisation to address issues such as drift, hallucinations and latency; incident investigation and resolution
What They're Looking For.
Must Have
Previous experience in AI, data science, ML engineering or advanced analytics, hands-on experience designing, building and deploying Copilot and/or agentic AI solutions (e.g. Microsoft 365 Copilot extensions, Azure OpenAI-based copilots, custom AI assistants/agents), proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit-learn, pandas, NumPy), Proven experience integrating AI services with enterprise systems via APIs and event-driven architectures, Practical experience with LLMs, prompt engineering, RAG and tools/plugins for agents and copilots, Familiarity with cloud platforms (ideally Azure) and AI services (e.g. Azure OpenAI, Azure Machine Learning, or equivalents), Experience working in agile, cross-functional delivery teams
Nice to Have
Postgraduate study or certifications in AI, machine learning or data science, Cloud certifications (e.g. Azure, GCP, AWS) and relevant AI/ML credentials, Experience with big data and distributed computing (e.g. Spark, Databricks, Hadoop or cloud-native alternatives), Experience with containerisation and DevOps/MLOps tools (e.g. Docker, Kubernetes, Git, CI/CD, MLflow, Airflow), experience with data engineering concepts (ETL/ELT, data integration, warehousing, vector databases/search)
What You'll Do.
Design and implement AI copilots and agentic AI solutions
Translate business use cases into Copilot scenarios
Build and maintain AI components
Implement end-to-end MLOps pipelines
Integrate AI agents with enterprise systems
Collaborate with data engineers to design data pipelines
logging and analytics
Lead optimisation to address issues such as drift
hallucinations and latency
Contribute to AI engineering standards
guardrails and best practices
Support incident investigation and resolution
Ensure solutions comply with security
compliance and ethical AI requirements
How You'll Work.
Team & Collaboration
Working closely with technology and business teams; Collaborate with data engineers; Contribute to AI engineering standards, guardrails and best practices; Support incident investigation and resolution with Service Delivery; Share knowledge and mentor colleagues to build AI literacy and capability across IT and the wider business; Experience working in agile, cross-functional delivery teams
Communication Scope
Share knowledge
Process & Methodology
agile
Full Job Description
The AI Engineer designs, builds and operates scalable, secure AI solutions for JCDecaux UK, with a focus on Copilot implementations and agentic AI that augment users and automate complex workflows. The role converts business and data requirements into production-grade AI assistants, copilots and intelligent agents embedded into products, processes and decision making. Working closely with technology and business teams, the AI Engineer oversees solutions from experimentation through to deployment, optimisation and support, ensuring they integrate with JCDecaux UK’s digital, data and technology landscape. The role supports JCDecaux UK’s vision and mission by using advanced AI to pioneer real-world communications and enhance client and consumer understanding. Reports to: Chief Innovation and Technology Officer **What you 'll be doing...** * Design and implement AI copilots and agentic AI solutions that assist users, automate multi-step tasks and orchestrate calls to internal tools and systems. * Translate business use cases into Copilot scenarios, prompt flows, connectors and agent behaviours, defining secure, scalable solution architectures. * Build and maintain AI components (e.g. RAG, classification, recommendation, summarisation) using Python and modern ML/LLM frameworks. * Implement end-to-end MLOps pipelines for development, testing, deployment and monitoring of Copilot and AI solutions, and deploy them into production environments (e.g. Microsoft 365 Copilot, Azure, internal apps). * Integrate AI agents with enterprise systems (e.g. CRM, ERP, scheduling, inventory, data platforms) via APIs and microservices. * Collaborate with data engineers to design data pipelines, retrieval layers (vector stores, search indices) and large-scale processing using big data frameworks. * Implement monitoring, logging and analytics to track usage, performance, quality and user satisfaction, and lead optimisation to address issues such as drift, hallucinations and latency. * Contri
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