Principal AI Engineer

About the role

We are looking for a Principal AI Engineer to lead the design and implementation of advanced AI solutions across our product and business ecosystem. You will define an organisation‑wide AI strategy, combining hands‑on technical work with cross‑functional influence to drive measurable impact.

Key responsibilities

• Design, build and deploy AI‑powered systems that enhance product functionality and user experience.
• Develop and integrate agentic frameworks, Retrieval‑Augmented Generation (RAG) pipelines, and vector‑database architectures for natural‑language and automation use cases.
• Fine‑tune and customise large language models (e.g., OpenAI, Anthropic) for specific business applications.
• Collaborate with engineering and data‑science teams to implement MLOps best practices, from deployment to monitoring and continuous iteration.
• Partner with commercial and operational teams to identify processes that can be automated through AI tools.
• Ensure responsible and secure AI use via data governance, model guardrails and compliance measures.

Required profile

• Deep expertise in Python, machine learning and data science.
• Proven experience building, deploying and scaling AI models in Azure and/or AWS environments.
• Skilled in LangChain, LangGraph, vector databases and prompt engineering.
• Strong understanding of LLM optimisation, context extension and RAG‑based frameworks.
• Excellent cross‑functional collaboration and ability to communicate complex AI concepts to non‑technical stakeholders.
• Proactive, creative mindset with the autonomy to build production‑grade AI systems.
• Advanced degree (MSc/PhD) in Computer Science, Data Science or related field is a plus.

Required skills

• Python
• Machine Learning
• Data Science
• Azure
• AWS
• LangChain
• LangGraph
• Vector Databases
• Prompt Engineering
• LLM fine‑tuning (OpenAI, Anthropic)
• MLOps
• RAG pipelines
• Agentic frameworks

What we offer

• Central role in defining and executing an organisation‑wide AI roadmap.
• Direct collaboration with senior leadership on strategy and implementation.
• Hybrid working environment balancing deep technical focus and teamwork.
• Competitive compensation in a high‑growth, data‑rich environment.