Robots & Pencils

Product Manager

• Own and manage the product backlog, ensuring work is clearly defined, prioritized, and aligned to business outcomes
• Translate business needs and stakeholder requests into structured requirements, user stories, and acceptance criteria
• Partner with engineering and design to ensure requirements are well understood and delivered with quality
• Facilitate sprint planning, backlog refinement, and day-to-day delivery execution
• Identify and manage dependencies, risks, and scope changes throughout the delivery lifecycle
• Use data, user feedback, and team insights to continuously improve the product
• Use AI tools such as Claude to accelerate documentation, research, and analysis
• Build and maintain strong relationships with client stakeholders
• Communicate progress, risks, and tradeoffs to technical and non-technical audiences
• Facilitate working sessions, requirements discussions, and decision-making forums
• Own delivery outcomes and frame requests around user and business outcomes
• Contribute to a positive, high-performing team environment

Senior Product Manager

Data Engineer

• Define data architecture and platform strategy across pipelines, warehouses, and data lakes
• Build and optimize scalable batch and real-time data pipelines
• Define and enforce data governance, quality standards, and compliance frameworks
• Build monitoring, logging, and alerting for data pipelines and services
• Contribute to CI/CD workflows for data deployment and automation
• Drive data platform modernization for performance, cost, and scalability
• Use Claude, Cursor, and other modern AI assistants to ship higher-quality work
• Design and implement data contracts and event flows with backend, platform, and engineering teams
• Lead data pipelines for production AI/ML systems, including embeddings, vector stores, RAG data preparation, feature stores, and training/inference data flows
• Integrate data services with APIs, middleware, and third-party systems
• Partner with leadership on data strategy
• Collaborate with engineering, analytics, AI, and product teams
• Advocate for data quality, governance, and platform best practices
• Establish data engineering standards across the team
• Mentor junior and mid-level engineers
• Make high-stakes architectural decisions with clear ownership and consideration of long-term tradeoffs