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

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

Data Scientist

Key skills