Jobs at Pyyne

Develop and maintain Python features and services for a custom AI intelligence solution. Build async REST APIs, work with PostgreSQL and ORMs, write automated tests, and deliver small, well-tested increments. Collaborate with a senior engineer on architecture, support LLM and RAG components, communicate proactively with clients, and adapt to changing priorities. The role is fully remote for candidates in Brazil or Argentina.

Own recurring finance and people operations, including bookkeeping, monthly close, payroll, benefits administration, client invoicing, receivables, expense management, and process documentation. The role supports US and international employees and contractors across multiple countries, reconciles financial data, administers payroll and benefits platforms, and maintains accurate reporting. It requires hands-on QuickBooks Online and US payroll experience, strong confidentiality, fluent English, and availability during US Eastern business hours from Campinas.

The Financial Controller will own full-cycle accounting, monthly and quarterly close, multi-entity reporting, billing, collections, payables, payroll, benefits administration, reconciliations, compliance filings, audit support, financial reporting, cash-flow forecasting, expense management, and operating metrics. The role reports to the COO and supports leadership with financial strategy, modeling, board-level reporting, and ad hoc analysis in a global professional services environment.

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.