Senior / Staff AI Engineer (Systems & Architecture)

Role Overview

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We're seeking a Senior/Staff AI Engineer(s) to join our fast-paced team to design, develop, and implement new features for [Littlebird](https://www.joinlittlebird.com/), our personalized AI teammate for Mac and Android (Windows soon!). We’re building personal AI; a thought partner that connects dots in your work and helps you think. Check out the recent [TechCrunch news on our $11M seed funding](https://www.linkedin.com/feed/update/urn:li:activity:7442288049939533825) and what users are saying about the product.

We're an async-first team that values craft and ownership. Our engineers live at the intersection of genuine research curiosity and production discipline: you'll push the frontier in areas like conversational inference, memory, and sentiment analysis, then wrestle those ideas into systems that are fast, lean, and built to scale.

The Role

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You will architect the system that allows our agent to reason, remember, and evolve. You'll develop core infrastructure that turns messy, unstructured user data into a coherent world model.

Some of the hard problems you'll solve:

• Build a Real AI Memory (Beyond Vectors): Our current vector-based memory is hitting its limits. You'll lead the charge to design and implement our next-generation memory system This means solving hard problems in:
• Entity & Relationship Extraction: How do you reliably extract "my sister Anna" and the "Q4 roadmap" as distinct entities and link them from unstructured text, at scale?
• Temporal Awareness: How do you model facts that change over time? A user's project status, their job title, their relationship to a contact—these aren't static. You'll build the systems to manage this temporal complexity.
• Graph-based Retrieval: How do you query a graph efficiently to provide the agent with rich, structured context, moving beyond simple semantic search?

• Architect a Scalable, Debuggable Agentic System: Our agent is a multi-step, tool-using system.
• You'll design clean interfaces between the agent's "brain" (the planner) and its "hands" (the tools/modalities).
• You'll build the debugging and observability tools necessary to understand _why_ an agentic flow failed, which is one of the hardest challenges in this space.

• Scale Our Data & Retrieval Pipelines: As we grow, you'll be responsible for ensuring our data ingestion, hybrid search (BM25 + vector), and re-ranking pipelines are fast, reliable, and cost-effective.

Required Skills

• Deep experience building and scaling data-intensive backend systems in Python.
• A strong mental model for data structures and their trade-offs. You like to think deeply about how to represent complex information.
• Hands-on experience with RAG pipelines, but you're probably a little frustrated with their limitations.
• A pragmatic approach. You know when to build for the long term and when to ship a clever solution that works now.

Benefits

• 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
• We love to hear when birds chirp!