AI Engineer

Description

Here at Lusha, we power sales teams with data. Over 1.5M users and teams at Google, Spotify, and many more, use our platform to find verified contacts, spot real-time buying signals, and automate workflows with 200M+ records.

As an AI Engineer on our Search Engine team, you’ll help build the state-of-the-art, powered-by-AI search. You’ll design and operate high-performance services that transform user intent into fast, accurate, and reliable results. Your work sits at the foundation of how customers discover companies and contacts, delivering a seamless, intelligent search experience at scale.

What You'Ll Actually Do:

• Build lightning-fast APIs serving recommendations, contact, and company data to millions of users daily.
• Design event-driven systems that sync data across products and data lakes in real-time.
• Develop agentic flows and integrate AI solutions that optimize user experience.
• Optimize data retrieval, caching, and indexing for sub-second response times at scale.
• Create fault-tolerant services with robust monitoring and CI/CD that just work.
• Collaborate with Data Scientists and ML engineers to power AI-driven features and pipelines that customers use.

Requirements

• Backend engineers with 4+ years building production APIs and large-scale data systems
• Polyglot developers fluent in Python and/or Node.js with strong performance optimization skills.
• Strong hands-on experience with Elasticsearch (mappings, analyzers, tuning) and vector search for low-latency semantic retrieval.
• Experience integrating LLM capabilities into backend workflows, including basic prompt and context engineering.
• Solid understanding of CI/CD, observability, distributed systems, and scalable service patterns.
• Ability to work with React, handle UI exceptions, and collaborate on micro-frontend components when needed.
• Ability to work on projects independently and collaborate in a team environment.

Nice To Have

• Strong background with embedding models, embedding evaluation, RAG, and high-volume similarity search workflows.
• Experience building evaluation pipelines and optimizing low-latency inference flows combining LLM calls, embeddings, vector search, and multi-step orchestration.
• Experience designing and implementing data retrieval systems (smart filters, semantic ranking) and contributing to React micro-frontends that expose these capabilities.

Ready to build the search engine that drives revenue? Apply now.