Systems & Infrastructure Engineer

About Us and the Problem

 

We're building the best search for AI.

Search is becoming the core primitive for AI. Every agent workflow, every reasoning system, every tool call needs context from the web and beyond, but today's search infrastructure was built for a different era. We're building the stack that makes the web accessible to how agents actually work: content at scale, structured for reasoning, designed for deep research across thousands of sources. Information Retrieval is in a renaissance, LLMs are changing not just what we need to build but how we can build it, and we combine first-principles research with hard engineering to solve web-scale indexing for agentic use.

How agents access the web is one of the foundational questions of the next decade of software, and the infrastructure is what makes the answer fast, cheap, and possible at scale. You'd be building the layer underneath everything: storage, retrieval, indexing, serving. The kind of work that ends up in papers and the kind of work that ends up running in production, often the same week.

What You'll Be Doing

Own critical infrastructure end-to-end: Take a layer of the stack (search and storage, data lake, ingestion, serving, or ML systems) from architecture through production.

Set the technical direction: Make the hard calls on storage formats, query algorthims, scheduling models, and cost vs latency trade-offs that the team will live with for years.

Engineer at petabyte scale: Drive concurrency, networking, IO, caching, scheduling, query latency, and cost down to the last percent.

Who You Are

A mid to senior-level engineer with 3+ years building, shipping, and operating systems-intensive infrastructure in production.

Deep experience in distributed systems, operating systems, networking, databases, data engineering, search infrastructure, or ML systems with the judgement and taste that comes from having owned them at scale.

Our systems are written in Rust and Python. You must be fluent in these and other systems languages (C, C++, Go) are a bonus.

Comfortable working with cloud infrastructure, containerised workloads, Kubernetes, and large compute environments.

Have made architectural decisions you've had to live with, and know what you'd do differently next time.

Strong builder who wants meaningful ownership over real infrastructure and is comfortable using AI tools as part of their engineering workflow.

Bonus Points

Prior experience scaling infrastructure at a search, large-scale data, or ML company.

Track record of owning production systems at scale.

Have built or significantly contributed to open-source infrastructure projects (databases, distributed systems, data engines).

Published research, conference talks, or writing on systems, IR, or ML infrastructure.

Experience with GCP, AWS, Kubernetes, Terraform, observability, workload orchestration, or large distributed worker pools.

Experience with search databases, vector databases, retrieval systems, feature stores, training pipelines, or evaluation infrastructure.

Be cracked.

Why Join

We are a small team with few abstractions between you and the system you're building. The infrastructure is the product, what you ship is the infrastructure agents run on. As a senior hire, you'll shape the direction of a foundational layer, not just contribute to it.

If you want to build systems that will serve as core primitives for agents, reach out: careers@valyu.ai