Senior Backend Engineer

Littlebird
3dRemote

About The Position

We're seeking a Senior Backend Engineer to join our fast-paced team to design, develop, and implement new infrastructure 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. 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 realtime data, search, and inference, then wrestle those ideas into systems that are fast, lean, and built to scale. 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 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: 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. Security: Ensure our infrastructure is highly secure and observable, with a focus on speed and cost 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.

Requirements

  • Deep experience building and scaling data-intensive backend systems in Python or Go.
  • Strong system-design skills and experience working with distributed systems.
  • A clear 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, even if you're a little frustrated with their limitations.
  • Production experience with modern cloud infrastructure, observability tooling, and PostgreSQL
  • A pragmatic approach. You know when to build for the long term and when to ship a clever solution that works now.

Responsibilities

  • Architect the system that allows our agent to reason, remember, and evolve.
  • Develop core infrastructure that turns messy, unstructured user data into a coherent world model.
  • Build AI Memory (Beyond Vectors)
  • Scale Our Data & Retrieval Pipelines
  • Ensure our infrastructure is highly secure and observable
  • Graph-based Retrieval
  • Architect a Scalable, Debuggable Agentic System
  • Design clean interfaces between the agent's "brain" (the planner) and its "hands" (the tools/modalities).
  • Build the debugging and observability tools necessary to understand why an agentic flow failed

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. 401k options for all US-based employees.
  • Flexible working hours across multiple time zones
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