Teams at Pythian

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Develop, deploy, and maintain scalable AI/ML pipelines and production models, including LLMs and generative AI. Optimize model performance, latency, and cost across AWS, GCP, and Azure. Apply MLOps practices such as CI/CD, versioning, monitoring, logging, and maintenance. Collaborate with data scientists, software engineers, solution architects, and cross-functional teams to integrate AI capabilities into products and workflows.

Lead the architecture and development of scalable AI/ML pipelines and production systems, including LLMs and Generative AI. Mentor engineering teams, guide technical decisions, operationalize models, optimize performance and costs, and implement MLOps practices such as CI/CD, monitoring, versioning, and maintenance. Partner with executives, clients, product managers, data scientists, and software engineers to align AI roadmaps with business goals and integrate ethical AI capabilities into enterprise applications.