Applied AI Engineer – Agent Intelligence, Retrieval

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🔥 20 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Littlebird

WebsiteLinkedInAll Job Openings

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.

📋 Description

• Design, develop, and implement new features for Littlebird, an AI teammate for Mac and Android • Evolve the hybrid search pipeline to scale with customer growth • Improve retrieval for broad queries through query analysis, decomposition, and multiple retrieval strategies • Experiment with and productionize re-ranking models to reduce latency bottlenecks • Optimize ranking by blending sparse and dense retrieval signals • Design and test context pruning and summarization techniques • Improve the agent's multi-step, tool-calling reasoning • Engineer prompt-level context structure to reduce hallucinations and improve reasoning • Debug agent failures across tool calls, context retrieval, and LLM responses • Collaborate within a small, async-first engineering team and contribute to infrastructure decisions

🎯 Requirements

• Strong OOP programming skills and prior experience writing production software in Python, TypeScript, or C++ • Deep, intuitive understanding of information retrieval and modern RAG pipelines • Experience building information retrieval and RAG pipelines from scratch • Hands-on experience with vector databases, hybrid search, and re-ranking models • Experimental, data-driven mindset, including running A/B tests, analyzing metrics, and iterating quickly • Pragmatic approach focused on shipping tangible improvements to AI quality

🏖️ 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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