Jobs 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.

Performs manual and basic automated testing for consumer mobile, web, and API products. The QA Tester plans and executes tests, validates features against specifications, investigates post-launch defects, and helps engineering teams prioritize high-impact quality issues. The role uses bug tracking, test management, build-management, mobile development, and command-line tools while collaborating with global product teams. Native Spanish and fluent English are required, with Postman, proxy tools, IDE navigation, and SQL experience preferred.

Lead and facilitate Agile ceremonies, remove blockers, and drive delivery for cross-functional engineering teams. Align product and engineering execution with strategic goals, track progress using Agile metrics, support QA and demos, and coordinate distributed teams across the software development lifecycle. Use tools like JIRA and AI assistants to improve productivity and team outcomes.