Lead the end-to-end development and deployment of AI/ML projects, ensuring they solve real-world engineering and consultancy challenges
Design and implement Agentic AI architectures (using LangChain, Lang Graph, etc.) to automate complex reasoning tasks across technical documentation and project management
Rapidly develop Proof of Concepts (PoCs) and transition them into high-availability, enterprise-grade applications hosted on Azure
Work alongside structural engineers, environmental consultants, and digital architects to integrate AI/ML into the wider ecosystem
Contribute to the scale-up of AI solutions, ensuring cost-optimized deployment (LlmOps) and alignment with our commitment to ethical & responsible AI

5+ years of experience in working with NLP problems
2+ years of experience in working with LLM
Proven experience fine-tuning and deploying LLM models (GPT, Llama 3, Falcon) and proprietary models via Azure AI Foundry
Hands-on experience with agentic AI orchestration design patterns with building systems using LangChain, Crew AI, or Llama Index
Mastery of RAG (Retrieval Augmented Generation), RAG Fusion, and Chain-of-Thought prompting to extract insights from massive technical datasets
Deep understanding of Transformers (BERT, GPT), NLU, and NLG principles
5+ years of experience with algorithms including XGBoost, Random Forest, and advanced regression models/time series models
Proficiency in Python with a focus on clean code, design patterns, and scalable architecture
Practical experience with PyTorch or Keras for computationally intensive modelling
Strong track record of deploying models within Azure ML and managing the full ML lifecycle
Experience with Vector Databases (Pinecone, Milvus, or PgVector) and Graph Databases to support complex data relationships
Knowledge of LlmOps, Docker, and Kubernetes to ensure model reliability and cost-efficiency
Collaborative mindset
Sustainability focus
Leadership behaviour
Agile advocate

Assistant – Graduate IT Data Specialist

Key skills