Applied AI Engineer - Agent Intelligence & Retrieval
Full-timeSenior
AI Tools
Hybrid SearchRAGRe-rankersVector Databases
Tech Stack
PythonTypeScriptC++RAGVector DatabasesBM25Hybrid SearchRerankingAI Agents
Agent Workflow
Hybrid retrieval (BM25 + vector + RRF + reranker) and agent flow debugging for a cross-platform AI teammate product.
About the Role
Littlebird is hiring an Applied AI Engineer to join our fast-paced team, designing, developing, and implementing new features for Littlebird, the AI teammate for Mac and Android.
About the Role
This role is about making our agent smarter, faster, and more reliable. Your focus is the quality of retrieval, the precision of ranking, and the logic of the agent. You'll own the evolution of our hybrid search pipeline and debug complex agentic flows across layers of tool calls, context retrieval, and LLM responses.
Key Responsibilities
- Own the evolution of our hybrid search pipeline (BM25 + vector + RRF + re-ranker).
- Optimize the structure and presentation of context to minimize hallucinations and improve reasoning.
- Debug complex agentic flows by tracing root causes through layers of tool calls, context retrieval, and LLM responses.
- Ship improvements grounded in A/B tests and performance analysis.
Requirements
- Strong OOP programming skills and prior experience writing production software in Python, TypeScript, or C++.
- A deep understanding of information retrieval and modern RAG pipelines.
- Hands-on experience with vector databases, hybrid search, and re-ranking models.
- An experimental, data-driven mindset comfortable with A/B tests and performance analysis.
- A pragmatic approach focused on shipping tangible improvements.
Benefits
- Competitive compensation including stock and health benefits.
- Paid time off and parental leave.
Location
Remote, based in the USA.
