Teams at Pyyne

Build and maintain Python backend systems for an AI-powered research platform. Develop data ingestion pipelines, integrate LLMs and agentic workflows, and ensure production reliability, performance, and data integrity. Translate client workflows into scalable technical solutions, manage roadmap priorities, collaborate across engineering functions, and engage with technical and non-technical stakeholders. The role offers opportunities to influence architecture and grow into technical leadership.

Conduct product analysis, answer stakeholder questions, define product metrics, and design and evaluate A/B tests. Partner with product managers and engineers, explain statistical concepts, assess significance and experimentation pitfalls, and provide data-driven insights. The role also involves understanding data models, communicating findings through data storytelling, supporting product decisions, and contributing to team process improvements.

Lead design and implementation of backend services and scalable data pipelines, own orchestration and CI/CD, architect data warehousing, mentor junior engineers, contribute to AI feature integration, maintain documentation and Git workflows, and participate in client-facing architecture decisions.