Search Engineer, AI Infrastructure (SF)

Lavendo, Inc.; United States; On-site; USD 235,000 - 260,000; Full time

Benefits offered by this job

Equity

100% employer-paid health/dental/vison

PTO 15+ days

Parental leave 12 weeks

Learning & development budget

Wellness stipend

Job summary

Lavendo, Inc. partners with startups to hire top-tier talent. Our client builds the data layer that AI agents run on, turning URLs into clean, structured data.

As a Search Engineer, you will own ranking and relevance for a high-quality, scalable open web search system, addressing freshness, deduplication, latency, and cost. You will work directly with the Head of Search and a small team to shape the roadmap, improve crawling, indexing, retrieval, and serving infrastructure, and ship measurable

Qualifications

• 3+ years building and operating production search or retrieval systems, with direct ownership of ranking and relevance.
• A specific example of a ranking or reranking change you owned and the measurable impact it had on relevance, recall, conversion, CTR, NDCG, MRR, or a similar metric
• Hands-on information-retrieval depth across BM25/lexical, semantic/vector, hybrid retrieval, reranking, and retrieval or RAG evaluation
• Strong backend and distributed-systems skills in Go, Rust, Python, or a comparable language, with end-to-end production ownership
• Experience improving latency and cost at meaningful query volume while maintaining quality and reliability
• Familiarity with search and infrastructure tooling such as Lucene, Elasticsearch, OpenSearch, Redis, Kafka, PostgreSQL, Kubernetes, Docker, AWS/GCP, gRPC, or Protobuf

Responsibilities

• Own ranking quality and relevance for LLM-driven search and retrieval
• Build and operate the crawling, indexing, retrieval, and search-serving systems behind the product.
• Improve search quality using lexical, semantic, hybrid, and reranking approaches
• Reduce latency and cost per query as query volume and corpus size grow, without compromising relevance, correctness, or reliability
• Own systems end to end: design, build, deploy, monitor, troubleshoot, measure, and iterate in production
• Solve for freshness, incremental indexing, deduplication, crawl scheduling, and large-scale corpus management
• Work directly with the Head of Search and the team to shape the roadmap and ship customer-facing improvements quickly

Skills

Ownership of ranking & relevance

Information retrieval depth

Backend & distributed systems

Latency & cost optimization

Go/Rust/Python

Lucene/Elasticsearch/OpenSearch

Tools

Lucene

Elasticsearch

OpenSearch

Redis

Kafka

PostgreSQL

Kubernetes

Docker

AWS/GCP

gRPC/Protobuf

Job description

Lavendo partners with startups and high-growth companies to help them hire top-tier sales, GTM, and technical talent. This role is with one of our clients; we'll share full details about the company and interview process as we get to know you and confirm mutual fit.

About the Company

Our client builds the data layer that AI agents run on. One API call turns any URL into clean, structured, LLM-ready data. It is already the default way a huge number of developers pull web data into their AI systems.

The numbers back it up: 8 figures in ARR in year one, more than doubled that in year two, and 125,000+ GitHub stars. They just closed a $75M Series B. The company is small, moving fast, and hiring people who want to build the next chapter with them.

The Mission

They believe developers and AI agents should not have to fight the web to get useful data out of it. Every hour spent maintaining a scraper, dealing with stale pages, or working around brittle retrieval systems is an hour taken away from the actual product.

Their job is to make that problem disappear: give AI systems reliable access to the live web, then make the results clean, current, structured, and useful enough to power real products.

The Opportunity

As a Search Engineer, you will own the systems that turn the open web into a high-quality search index.

You will work directly with the Head of Search and a small team to build and improve the crawling, indexing, retrieval, ranking, and serving infrastructure behind a fast-growing search product. This is an end-to-end role: you will improve relevance while solving the real constraints of search at scale - freshness, deduplication, latency, reliability, and cost per query.

The key requirement is direct production ownership of ranking and relevance. You should be able to point to a search-quality change you personally shipped and the metric it improved.

What You'll Do

• Own ranking quality and relevance for LLM-driven search and retrieval
• Build and operate the crawling, indexing, retrieval, and search-serving systems behind the product.
• Improve search quality using lexical, semantic, hybrid, and reranking approaches
• Reduce latency and cost per query as query volume and corpus size grow, without compromising relevance, correctness, or reliability
• Own systems end to end: design, build, deploy, monitor, troubleshoot, measure, and iterate in production
• Solve for freshness, incremental indexing, deduplication, crawl scheduling, and large-scale corpus management
• Work directly with the Head of Search and the team to shape the roadmap and ship customer-facing improvements quickly

What You Bring

• 3+ years building and operating production search or retrieval systems, with direct ownership of ranking and relevance
• A specific example of a ranking or reranking change you owned and the measurable impact it had on relevance, recall, conversion, CTR, NDCG, MRR, or a similar metric
• Hands-on information-retrieval depth across BM25/lexical, semantic/vector, hybrid retrieval, reranking, and retrieval or RAG evaluation
• Strong backend and distributed-systems skills in Go, Rust, Python, or a comparable language, with end-to-end production ownership
• Experience improving latency and cost at meaningful query volume while maintaining quality and reliability
• Familiarity with search and infrastructure tooling such as Lucene, Elasticsearch, OpenSearch, Redis, Kafka, PostgreSQL, Kubernetes, Docker, AWS/GCP, gRPC, or Protobuf

Key Success Drivers

The people who do well here have personally owned search quality in production, think end-to-end about relevance, crawling, indexing, serving, latency, and cost, and thrive in ambiguity by shipping, measuring, and iterating quickly without needing a fully defined playbook.

Why Join?

• Compensation & Equity: Base salary of $235K-$260K+. Meaningful equity in a fast-growing, well-funded startup
• Traction: 8 figures in ARR in year one, more than doubled in year two. 125,000+ GitHub stars and a developer base showing up before you even start selling to them. $75M Series B closed in 2026, backed by top-tier investors
• Team: ~40 people total, real visibility with the founders and leadership. No layers, no committees, fast decisions, short feedback loops
• Benefits: 100% employer-paid medical, dental, and vision (50% for spouse and kids); employer-paid life, short-term, and long-term disability insurance; 401(k), pre-tax FSA, and commuter benefits; pet insurance; 15+ days PTO; 12 weeks fully paid parental leave for moms and dads; $100/month wellness stipend; $1,000/year learning and development budget; 3-month paid sabbatical after 4 years; team offsites twice a year; SF HQ perks and a loaner e-bike for commuting
• Visa: not open to visa sponsorship on this one (US citizens and Green Card holders only).

Interviewing Process

• Intro Chat
• Technical Chat
• Founders Chat
• Paid Work Trial

We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race,