
11 - 50 employees
🤖 Artificial Intelligence
☁️ SaaS
⚡ Productivity
🔥 Funding within the last year
💰 $11M Seed Round on 2026-03
Artificial Intelligence • SaaS • Productivity
Littlebird is an AI-powered productivity assistant and memory for work. It provides a single place for Chat, Meeting Notes, Routines, and an MCP (work memory) that integrates with the tools you use, offers a Hover integration to surface assistance in context, mobile and text access, and features focused on privacy and security. Littlebird is positioned for individuals and teams across roles—leadership, creative, technical, health, client-facing, research, and personal productivity—and emphasizes integrations and enterprise/team plans.
🔥 20 minutes ago
Where this job comes from
Posted on Littlebird's careers page, not through a job board
First seen by Remote Rocketship 20 minutes ago

11 - 50 employees
🤖 Artificial Intelligence
☁️ SaaS
⚡ Productivity
🔥 Funding within the last year
💰 $11M Seed Round on 2026-03
Artificial Intelligence • SaaS • Productivity
Littlebird is an AI-powered productivity assistant and memory for work. It provides a single place for Chat, Meeting Notes, Routines, and an MCP (work memory) that integrates with the tools you use, offers a Hover integration to surface assistance in context, mobile and text access, and features focused on privacy and security. Littlebird is positioned for individuals and teams across roles—leadership, creative, technical, health, client-facing, research, and personal productivity—and emphasizes integrations and enterprise/team plans.
• Design, develop, and implement new features for Littlebird, a personalized AI teammate for Mac and Android • Architect the system that allows the agent to reason, remember, and evolve • Develop core infrastructure that turns unstructured user data into a coherent world model • Design and implement a next-generation AI memory system beyond vector-based memory • Build entity and relationship extraction systems for unstructured text at scale • Model temporally changing facts and relationships • Build efficient graph-based retrieval for rich, structured agent context • Design clean interfaces between the agent planner and tools/modalities • Build debugging and observability tools for agentic flows • Scale data ingestion, hybrid search using BM25 and vector search, and re-ranking pipelines • Collaborate asynchronously across multiple time zones
• Deep experience building and scaling data-intensive backend systems in Python • Strong mental model for data structures and their trade-offs • Hands-on experience with RAG pipelines • Pragmatic approach to balancing long-term development with expedient solutions
• Remote-friendly work environment • Collaborative team culture • Opportunity to shape infrastructure decisions • Competitive compensation packages including stock and health benefits, paid time off, and parental leave • Flexible working hours across multiple time zones
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