Staff Systems Engineer, Rust / Data Infrastructure

Our client is looking for a Senior Systems Engineer to help refine the foundations of their platform and build the next generation of agent-first data infrastructure. You will join at a stage where engineers have a large influence and ownership on both the product and the engineering culture.

The bigger picture: today's leading data platforms were built for teams of human data scientists. Our client is building the next generation of that stack for a world where the primary user is a swarm of AI agents working on the same data at once, which means rebuilding storage, compute, and governance from first principles.

This role is based in NYC and flex-hybrid (around 3 days/week), as the company consolidates its core engineering team there (relocation welcome). This is one of several senior/tech-lead engineering roles the company is hiring right now as the team doubles.

You will work closely with experienced systems builders, database researchers, product designers, and the founding team to design and implement performant systems for running data workloads over object storage.

You will work across product abstractions, distributed systems, data management, and developer tooling. You will be expected to understand problems vertically: from what an agent is trying to accomplish, down to the runtime, storage, and correctness properties required to make it possible. The ability to learn quickly, make intelligent trade-offs, challenge conventional wisdom, and operate across blurry boundaries is essential.

Our client is looking for a senior engineer with at least 7 years of experience who's ready to operate as a tech lead. In their world that means someone who makes the call on technical decisions in their area and owns the outcome, while continuing to write code hands-on (under no circumstances does this person stop writing code). This is not a people-management focused role; they're looking for IC depth and technical ownership, and, ideally, someone who can help hire and mentor the rest of the team.

What you will do

Design

• Design systems that allow users to safely run, inspect, verify, and modify production-scale data workloads.
• Develop APIs and abstractions that are easy for humans to understand, and practical for agents to implement.
• Use production traces and agent behavior to identify opportunities for new system capabilities and optimizations.

Develop

• Implement performant systems for executing Rust, Python and SQL workloads over object storage.
• Improve the reliability, scalability, and efficiency of the runtime, working on scheduling, concurrency and caching.
• Improve the quality, security, observability, and iteration speed of the overall codebase.

Collaborate

• Help customers diagnose issues, debug workloads, and understand system behavior.
• Collaborate closely with product and design while retaining strong ownership of technical decisions.
• Share work with engineering and research communities through talks, papers, blog posts, and open-source releases.

First 30 days

• Get comfortable with the architecture, codebase, tooling, and deployment process.
• Understand the main production workflows end-to-end.
• Ship a small feature or meaningful improvement.

By 60 days

• Take ownership of one area of the platform and contribute actively to technical decisions.
• Debug real production issues and improve reliability, performance, or developer experience.
• Start working with junior members of the team, establishing trust and shared engineering standards.

By 90 days

• Make meaningful improvements to existing systems with increasing independence.
• Lead the design of a significant new capability.
• Become a trusted leader in both operational and technical discussions.

What our client is looking for

You are an experienced engineer who enjoys building simple abstractions over complex distributed systems. You should be excellent at:

• Their lingua franca is Python, and they use a lot of Rust, but they're open to anyone who can demonstrate outstanding equivalent experience in relevant systems.
• Designing, implementing, and operating distributed systems.
• Concurrency, asynchronous programming, fault tolerance, and failure recovery.
• Building cloud-based infrastructure.
• Modern software-engineering practices, including Git, containers, infrastructure as code, CI/CD, testing, security, and observability.
• Reading and writing technical design documents.
• Leading technical discussions and communicating trade-offs at different levels of abstraction, mentoring younger engineers through technical leadership.
• Taking ownership of ambiguous problems from initial requirements through production operation.

You should have working knowledge of:

• SQL and relational data systems.
• Object storage and cloud-native storage architectures.
• Distributed computation, whether through Kubernetes, Spark, query engines, or custom infrastructure.
• API and developer-tooling design.

Finally, while not necessary, experience in one or more of the following areas would be especially valuable:

• Database internals, query planning, execution engines, or optimization.
• Apache Arrow, DataFusion, DuckDB, or related systems.
• Transaction processing, Apache Iceberg, or data catalogs.
• Serverless runtimes, function scheduling, or sandboxed execution.
• Type systems, formal methods, or distributed-systems simulation.
• Infrastructure for coding agents, agent evaluation, or autonomous software development.

We don't expect one person to have experience across all these areas. They care more about strong fundamentals, intellectual curiosity, technical judgment, and the ability to learn unfamiliar systems quickly.