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Come join Naboo | Enterprise Context Layer for AI Agents & Developers!
About Naboo
At Naboo.ai, we harness the power of artificial intelligence to transform data into actionable insights. Our cutting-edge platform integrates advanced analytics and machine learning, enabling businesses to streamline operations, enhance customer experiences, and drive innovation.
We provide an AI context layer that feeds engineering and agent workflows with precise, intent-aware data from code, logs, tickets, and documentation. Unlike generic retrieval stacks, Naboo maps software context, so AI agents and copilots can execute actions reliably instead of guessing. Our user-friendly tools empower teams to make informed decisions faster, adapt to market changes, and unlock new growth opportunities.
Join us on our mission to make intelligent decision-making accessible for everyone. Naboo | Enterprise Context Layer for AI Agents & Developers
Software Engineer | Position Overview
In this role, you will build the core engine underneath Naboo: high-throughput indexing pipelines, graph traversal algorithms, hybrid retrieval (lexical + vector + graph), and low-latency query execution. This is deep systems and data engineering, not prompt engineering - the hard problems are retrieval precision, latency, and context density at enterprise scale.
Job Duties and Responsibilities
• Core Engine & Real-Time Data Pipelines: Design, build, and scale data pipelines, live ETL processes, and indexing engines that continuously pull and unify data from multiple customer integrations into a single knowledge graph, in real time - plus the graph-traversal systems that transform enterprise artifacts into that unified graph.
• Retrieval & Relevance: Optimize hybrid retrieval (BM25, dense embeddings, graph expansion, reranking) to maximize precision and minimize token footprint for downstream agent execution.
• Evaluation & Benchmarking: Build offline and online eval frameworks to benchmark retrieval accuracy, latency, and agent task success against real enterprise workloads.
• Production Ownership: Share end-to-end ownership of core systems - from schema design and implementation to deployment, observability, and production reliability.
• Technical Direction: Collaborate closely with the team on architectural decisions as agent paradigms (MCP, multi-agent coordination, context caching) rapidly evolve.
Skills You Must Have
• 3-5 years of experience building high-performance backend systems, distributed data pipelines, or data-intensive applications.
• Practical experience with retrieval & search: embeddings, vector search, lexical search (BM25 / Lucene / OpenSearch), and reranking trade-offs.
• Agentic SDLC practitioner: hands-on experience working in an AI-native development environment - actively using AI coding agents (Claude Code, Cursor, etc.) in your daily engineering workflow, designing with agent-first primitives, and dogfooding the paradigm we build for our customers.
• Product velocity: thrives in a fast-paced environment with high ownership, taking ambiguous technical problems from 0 to production. We're looking for people who identify problems and propose solutions on their own, rather than waiting to be told what to do. We encourage people to bring different ideas and value people who are not afraid to voice their opinion.