Artificial Intelligence Engineer

Are you an AI Engineer who can design, build, and deploy production-grade AI applications and agentic systems, while balancing innovation with enterprise-grade reliability?

This role sits within a large-scale enterprise transformation programme in the Energy sector, focused on delivering AI-powered solutions that change how a global Communications function operates.

You’ll work across both AI applications and Agentic AI systems - building everything from knowledge assistants and content generation tools to autonomous agents capable of planning, reasoning, using tools, and completing complex workflows.

This is not a traditional machine learning role. The focus is on prompt engineering, retrieval design, agent architectures, evaluations, guardrails, and delivering production-ready AI systems on Azure.

Your Role as an AI Engineer:

You will own AI solutions end-to-end - from architecture and design through to deployment, evaluation, observability, and continuous improvement.

Working closely with business stakeholders, product teams, and platform engineers, you'll transform ambiguous business challenges into scalable AI solutions that deliver measurable value.

You'll contribute across both AI-powered applications and agentic systems, selecting the right design patterns and approaches for each use case rather than relying on a single framework or methodology.

What You'll Do:

• Design and build AI applications including prompt engineering, structured outputs, context engineering, and tool/function calling
• Develop Retrieval-Augmented Generation (RAG) solutions using modern retrieval and vector search techniques
• Design and implement agentic systems using approaches such as ReAct, plan-and-execute, reflection, graph-based workflows, and multi-agent orchestration
• Build agent infrastructure including memory management, state persistence, tool integrations, retries, and human-in-the-loop approval workflows
• Develop evaluation frameworks and quality metrics for AI systems
• Implement guardrails including content safety, prompt injection protection, PII detection, and output validation
• Monitor and optimise system performance, observability, latency, cost, and reliability
• Build integrations with Microsoft 365, SharePoint, Power BI, and Azure-based AI services
• Collaborate with product owners and business stakeholders to define and deliver AI use cases
• Document architectures, prompt strategies, evaluation results, and best practices

What You'll Bring:

• Strong software engineering experience using Python in production environments
• Hands-on experience building AI applications using OpenAI, Azure OpenAI, Anthropic, or open-weight models
• Experience designing and implementing agentic systems using frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Strong understanding of AI design patterns including ReAct, multi-agent systems, reflection, and plan-and-execute workflows
• Experience building retrieval systems and working with vector databases such as Pinecone, Weaviate, Qdrant, pgvector, or Azure AI Search
• Practical experience evaluating and measuring AI system quality, safety, and performance
• Knowledge of cloud platforms, containerised deployments, and Azure-based architectures
• Understanding of AI security, governance, data privacy, and responsible AI principles
• Strong stakeholder communication skills and ability to translate business requirements into technical solutions
• Experience operating within large enterprise environments

Why Join the Remobi community:

• Fully remote, b2b/freelance contracts
• Opportunity to work on large-scale AI transformation programmes delivering cutting-edge AI and agentic systems
• Access to a network of experienced AI, data, and engineering professionals across Europe

👉 Apply today:

If you're passionate about building reliable AI systems, designing intelligent agents, and delivering real-world AI solutions at enterprise scale, we'd love to hear from you!