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Lead AI engineer

Lead Engineer AI, RAG & Cloud Infrastructure

Are you an experienced engineer who combines software engineering, cloud infrastructure and Generative AI? Do you enjoy building production-grade AI solutions while providing technical direction and bringing teams together?

For a large international organisation, we are looking for a Lead Engineer to help shape and further develop a modern RAG-based chatbot platform.

This is a hands-on technical leadership role for someone who understands both the AI application layer and the underlying infrastructure required to run these solutions reliably at scale.

The role

You will join an engineering organisation responsible for an enterprise-grade platform that combines document processing, information retrieval and Large Language Models to deliver intelligent chatbot experiences to users.

The platform is continuously evolving. While parts of the existing document-processing environment are focused on stability and optimisation, the chatbot platform is actively being improved with a strong focus on quality, performance and new capabilities.

As Lead Engineer, you will help define the technical direction and ensure that ideas are translated into robust, scalable and maintainable solutions.

The engineering organisation operates through several autonomous workstreams. Following a recent organisational integration, an important part of your role will also be helping establish alignment across teams and creating a consistent engineering approach.

What you will do

  • Provide technical leadership across the AI, RAG and cloud platform
  • Design, develop and improve production-grade RAG and LLM solutions
  • Work with document processing, embeddings, vector search and information retrieval
  • Improve the quality, accuracy, performance and reliability of chatbot solutions
  • Design and maintain scalable cloud infrastructure and platform services
  • Develop APIs, integrations and distributed services using modern engineering practices
  • Drive best practices around CI/CD, Infrastructure as Code, security and observability
  • Identify architectural and technical improvements and turn them into actionable initiatives
  • Work closely with software engineers, AI specialists, platform engineers and product stakeholders
  • Provide technical guidance and support to multiple workstreams
  • Help create alignment between teams following a recent organisational integration
  • Communicate architectural decisions and technical concepts clearly to both technical and non-technical stakeholders
  • Remain hands-on and contribute directly to the engineering challenges of the platform

What we are looking for

We are looking for an engineering-first profile rather than a purely managerial or research-oriented AI professional.

You bring:

  • 4+ years of experience in software, cloud, platform or infrastructure engineering
  • Strong hands-on experience with Retrieval-Augmented Generation (RAG)
  • Experience developing applications using LLMs / Generative AI
  • Experience with production-grade AI, chatbot or knowledge-retrieval platforms
  • Strong experience with cloud infrastructure, preferably Azure
  • Strong Python development experience
  • Experience with APIs, microservices and distributed systems
  • Knowledge of vector databases, vector search, embeddings and semantic search
  • Experience with document processing and information retrieval
  • Experience with DevOps, CI/CD and Infrastructure as Code
  • Experience taking technical ownership or acting as a Lead, Staff or Principal Engineer
  • Strong communication and stakeholder management skills
  • The ability to bring structure and alignment to complex environments
  • A pragmatic, proactive and delivery-focused mindset

Nice to have

Experience with one or more of the following is highly beneficial:

  • Azure OpenAI
  • Azure AI Search
  • Databricks
  • Kubernetes
  • Terraform
  • LangChain or LlamaIndex
  • MLOps / LLMOps
  • AI/RAG evaluation and quality frameworks
  • AI observability and monitoring
  • Enterprise-scale cloud platforms
  • Large-scale document processing environments