Data & AI
Today's scarcest skills, across both Europe and Asia-Pacific.
LLM Engineer
Specialist in deploying large language models — fine-tuning, retrieval-augmented generation (RAG), orchestration — against real business use cases. One of the scarcest profiles on today's AI market, in both Europe and Asia-Pacific.
AI Engineer
Designing and shipping AI systems into production, from prototype to scale. Demand is surging on both continents: AI/ML roles grew 151% in the UK between 2022 and 2025, and 176% in India over the same period — with a critical shortage of MLOps and GenAI talent everywhere.
ML Engineer
Building predictive machine learning models and the MLOps pipelines that put them into production, with growing emphasis on reliability, monitoring and model governance in regulated environments.
Agentic AI
Building autonomous AI agents able to execute complex tasks with minimal human supervision (frameworks such as LangGraph, AutoGen). Industry projections suggest a third of enterprise applications will embed agentic AI by 2028 — a still-emerging, and therefore especially scarce, skillset.
Data Scientist & Engineer
A dual profile increasingly sought by data leadership: predictive analysis and modelling on one side, data pipeline and infrastructure engineering on the other. Organisations are hiring people who can cover both ends of the chain rather than multiplying siloed specialists.
GenAI Engineer
Embedding generative AI into products and business workflows — text, image, voice — beyond the scope of large language models alone. A profile that bridges product and AI teams, increasingly sought as GenAI use cases move past the pilot stage.
Palantir Data Engineer
Specialist in the Palantir Foundry platform — ontology modelling, data integration and operational application deployment. A niche but tight market, driven by growing Palantir adoption across defence, industry and financial services.
Data Architect
Designing enterprise data architecture — data models, governance, and interoperability between legacy systems and cloud platforms. An increasingly strategic role as AI initiatives expose the limits of existing architectures.
Data & AI Strategy
Turning AI investment into concrete business decisions. Three profiles are in demand today: the strategist (business case, executive buy-in), the architect (RAG systems, compliance, legacy integration) and the AI governance/ethics specialist — a role that barely existed two years ago. The most active sectors: financial services, healthcare, manufacturing.