# Staff+ Software Engineer, VectorDB

**Company**: Anthropic
**Location**: New York City, NY
**Work arrangement**: hybrid
**Experience**: staff
**Job type**: full-time
**Salary**: $320,000-$485,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5458044008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_d18c88cf-065

## Description

Anthropic is looking for a Staff+ Software Engineer to work on the vector search infrastructure behind Claude. You will join a small team responsible for the vector database layer that serves Claude's retrieval workloads: its architecture, performance, scalability, and cost.

Key responsibilities:

- Own the core of Anthropic's vector database layer: index structures, storage layout, query execution, and the serving layer

- Own production readiness - benchmarking against exact search, capacity planning, onboarding new workloads, and the operational tooling to run it at scale

- Drive the recall, latency, and cost trade-offs - quantization, filtered search, index build and refresh strategy, and how compute and storage are separated and scaled

- Scale throughput by an order of magnitude as research and training demand grows, and work out whether the bottleneck is architecture, hardware, or engineering bandwidth

- Extend the retrieval stack toward hybrid retrieval - lexical search and fused ranking alongside vector search

- Set the evaluation methodology for the system - recall targets, latency objectives, cost per query, and the regression detection that keeps them honest

- Set technical direction for a growing team - lead design reviews, make architectural decisions others build on, and mentor the engineers joining the effort

- Share the on-call for the systems you own

Minimum qualifications:

- Direct experience building a vector database or approximate nearest-neighbor search system that ran in production at scale

- Deep knowledge of ANN index structures (graph-based, clustering-based, or disk-resident approaches), vector quantization, and filtered search

- Experience with search relevance and ranking

- Strong systems programming skills in a language such as Rust, C++, or Go, including performance-critical and memory-intensive code

- Experience designing and operating large-scale distributed storage or serving systems with strict latency and reliability requirements

- A track record of independently scoping and delivering ambiguous, multi-quarter technical projects

- Strong written and verbal communication, with experience driving alignment across teams with different priorities

- Interest in AI safety and Anthropic's mission

Preferred qualifications:

- Experience with object-storage-backed or disaggregated compute and storage database designs

- Experience building or operating full-text search engines (inverted indexes, BM25) or hybrid retrieval systems

- Familiarity with embedding models and the retrieval demands of LLM training and inference

- Experience using GPUs or other accelerators for index build or search

- Prior experience as a technical lead on a database or search infrastructure team

The annual compensation range for this role is $320,000-$485,000 USD.

## Skills

### Required
- vector database
- approximate nearest-neighbor search
- ANN index structures
- vector quantization
- filtered search
- search relevance
- ranking
- systems programming
- Rust
- C++
- Go
- distributed storage
- serving systems

### Nice to have
- object-storage-backed database designs
- disaggregated compute and storage
- full-text search engines
- hybrid retrieval systems
- embedding models
- LLM training
- inference
- GPUs
- accelerators

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/5458044008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)