ESSENTIAL SKILLS:

Architect and deliver production-grade AI systems spanning classical ML, LLM pipelines, RAG, agentic
orchestration, and context engineering.
Design and implement retrieval-augmented generation (RAG) architectures, including semantic caching,
contextual compression, hybrid retrieval and embedding pipelines.
Provide consultation on the architecture of agentic systems, including tool-calling architectures, multi-agent
workflows, agent memory design, and human-in-the-loop integration.
Develop and optimize large language model (LLM) capabilities: prompt and context engineering, fine-tuning,
LLM orchestration, and document intelligence workflows.
MLOps and delivery: model deployment, inference gateways, intelligent routing, monitoring, governance, and
performance optimisation for production systems.
Data engineering and production-scale processing: PySpark, ETL/ELT pipelines, API ingestion, unstru...