Lead development and productionization of large-scale ML and GenAI products. Own end-to-end data science lifecycle: prototyping, model development, benchmarking, deployment, monitoring, and stakeholder communication. Collaborate with domain experts to define metrics, optimize models (including LLM fine-tuning and embedding retrieval), and build scalable pipelines and integrations (OCR, table extraction, multimodal and GNN solutions).

The Lead Knowledge Engineer develops ontologies, knowledge graphs, and semantic artefacts, influencing data strategies and providing leadership for complex data integration projects.

Design, build and maintain cloud infrastructure and environments using Terraform and IaC; implement DevOps practices (containerization, CI/CD, monitoring); automate deployments; support and improve live applications and cloud account health; collaborate with development, testing, and client services.