Staff Infrastructure Software Engineer - Search Platform
To see similar active jobs please follow this link: Remote Development jobs
Role Description
As a Tech Lead Search Infra Engineer on the Search Platform team, you will be instrumental in designing, building, and scaling a next-generation search and retrieval platform from scratch. This platform will power Dropbox Dash, AI-driven search, Retrieval-Augmented Generation (RAG) pipelines, and AI agents, enabling intelligent, real-time information discovery and automation. This role requires deep expertise in search infrastructure, indexing, retrieval models, ranking optimization, and distributed systems. You will own the end-to-end development of search capabilities, including query execution, hybrid search (lexical, vector, and structured search), and real-time AI retrieval.
What’s the Impact? The search infrastructure you build will be mission-critical to Dropbox’s AI strategy. It will power intelligent assistants, real-time knowledge retrieval, and automation, driving AI adoption and engagement across the company’s product ecosystem.
Why Join? Define the future of Search & AI Retrieval by leading the development of an AI-driven search system from the ground up, powering intelligent assistants and AI agents. Work on cutting-edge infrastructure and machine learning, gaining deep exposure to search infra, RAG pipelines, and AI-powered knowledge retrieval. Operate at a massive scale, building a search platform that handles trillions of documents and serves millions of users worldwide. Join a collaborative, high-growth team where ownership, innovation, and impact are at the heart of everything we do.
If you are passionate about building high-performance search systems from scratch and pushing the boundaries of AI-powered search, this is the perfect role for you.
Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.
Responsibilities
Architect and Build Search from the Ground Up – Design and implement a highly scalable, AI-powered search and retrieval platform to support both traditional search and RAG-powered AI workflows.
Unify Search & AI Retrieval – Develop a single, cohesive search system that integrates with AI agents, copilots, and automated workflows, enabling intelligent search experiences.
Optimize Indexing & Query Execution – Scale high-performance indexing pipelines to handle trillions of documents while optimizing for latency, cost-efficiency, and relevance.
Power AI Agents & RAG Pipelines – Build real-time retrieval infrastructure that enables AI assistants to dynamically fetch, synthesize, and generate insights from structured and unstructured data.
Enhance ML-Driven Ranking & Relevance – Implement hybrid retrieval models (keyword, semantic, and structured queries), and embeddings-based search for AI interactions.
Scale Search & Retrieval for AI – Ensure global scalability, and multi-language support, adapting search experiences for diverse user needs.
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
Requirements
10+ years of professional software development experience as well as 5+ years of experience building and operating large-scale search platforms.
Expertise in search engine architecture, distributed indexing, retrieval models, and ranking optimization.
Proficiency in lexical search, vector search, embeddings-based retrieval, and hybrid search techniques.
Strong experience with Elasticsearch, OpenSearch, or custom search infrastructure.
Solid programming skills in Python, Go, C++, or Java, with distributed systems experience.
Familiarity with LLMs, AI-powered retrieval, and RAG pipelines is a plus.
Preferred Qualifications
Capable of articulating, conceptualizing, and defining comprehensive strategies
Exhibits a very high standard of technical judgement, innovation and execution to tackle open-ended problems that require difficult prioritization.
Proficiency in defining both objectives and the methodologies for achieving them.
Compensation
About the job
Staff Infrastructure Software Engineer - Search Platform
To see similar active jobs please follow this link: Remote Development jobs
Role Description
As a Tech Lead Search Infra Engineer on the Search Platform team, you will be instrumental in designing, building, and scaling a next-generation search and retrieval platform from scratch. This platform will power Dropbox Dash, AI-driven search, Retrieval-Augmented Generation (RAG) pipelines, and AI agents, enabling intelligent, real-time information discovery and automation. This role requires deep expertise in search infrastructure, indexing, retrieval models, ranking optimization, and distributed systems. You will own the end-to-end development of search capabilities, including query execution, hybrid search (lexical, vector, and structured search), and real-time AI retrieval.
What’s the Impact? The search infrastructure you build will be mission-critical to Dropbox’s AI strategy. It will power intelligent assistants, real-time knowledge retrieval, and automation, driving AI adoption and engagement across the company’s product ecosystem.
Why Join? Define the future of Search & AI Retrieval by leading the development of an AI-driven search system from the ground up, powering intelligent assistants and AI agents. Work on cutting-edge infrastructure and machine learning, gaining deep exposure to search infra, RAG pipelines, and AI-powered knowledge retrieval. Operate at a massive scale, building a search platform that handles trillions of documents and serves millions of users worldwide. Join a collaborative, high-growth team where ownership, innovation, and impact are at the heart of everything we do.
If you are passionate about building high-performance search systems from scratch and pushing the boundaries of AI-powered search, this is the perfect role for you.
Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.
Responsibilities
Architect and Build Search from the Ground Up – Design and implement a highly scalable, AI-powered search and retrieval platform to support both traditional search and RAG-powered AI workflows.
Unify Search & AI Retrieval – Develop a single, cohesive search system that integrates with AI agents, copilots, and automated workflows, enabling intelligent search experiences.
Optimize Indexing & Query Execution – Scale high-performance indexing pipelines to handle trillions of documents while optimizing for latency, cost-efficiency, and relevance.
Power AI Agents & RAG Pipelines – Build real-time retrieval infrastructure that enables AI assistants to dynamically fetch, synthesize, and generate insights from structured and unstructured data.
Enhance ML-Driven Ranking & Relevance – Implement hybrid retrieval models (keyword, semantic, and structured queries), and embeddings-based search for AI interactions.
Scale Search & Retrieval for AI – Ensure global scalability, and multi-language support, adapting search experiences for diverse user needs.
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
Requirements
10+ years of professional software development experience as well as 5+ years of experience building and operating large-scale search platforms.
Expertise in search engine architecture, distributed indexing, retrieval models, and ranking optimization.
Proficiency in lexical search, vector search, embeddings-based retrieval, and hybrid search techniques.
Strong experience with Elasticsearch, OpenSearch, or custom search infrastructure.
Solid programming skills in Python, Go, C++, or Java, with distributed systems experience.
Familiarity with LLMs, AI-powered retrieval, and RAG pipelines is a plus.
Preferred Qualifications
Capable of articulating, conceptualizing, and defining comprehensive strategies
Exhibits a very high standard of technical judgement, innovation and execution to tackle open-ended problems that require difficult prioritization.
Proficiency in defining both objectives and the methodologies for achieving them.