Senior (Rust) Infrastructure Engineer – Web Automation Platform for AIUMATR • Toronto, Ontario, Canada
Senior (Rust) Infrastructure Engineer – Web Automation Platform for AI
UMATR
- Toronto, Ontario, Canada
- Toronto, Ontario, Canada
Über
I'm working with a deeply technical, venture‑backed infrastructure startup building the web execution layer for AI‑native products. Their platform gives teams a high‑performance way to let AI systems reliably interact with complex websites and applications at scale, without having to own all the underlying browser and orchestration complexity themselves.
They've already reached strong product–market fit: a popular open‑source project with thousands of GitHub stars, a growing set of paying customers, and millions of workloads running through the platform each month, driven largely by an engaged developer community rather than heavy marketing. The engineering team is small, senior, and high‑ownership, and they're hiring experienced infrastructure engineers to help define how AI interacts with the web over the next decade.
Why this role
Work on foundational infrastructure that powers large‑scale AI workloads interacting with the web, with clear line of sight to 10x+ growth in traffic and complexity.
Tackle problems across virtualization, global orchestration, multi‑tenant isolation, and low‑latency web automation primitives.
Join as one of the early engineers, with real influence over architecture, roadmap, and engineering practices.
Ship open‑source tooling and APIs that are used and scrutinised by other engineers.
Competitive salary, meaningful equity, strong benefits, regular in‑person meetups, and a modern hardware setup.
What you'll be working on
Designing and operating globally distributed orchestration that can spin up and tear down isolated execution environments with very low startup latency.
Evolving multi‑tenant isolation models to safely run untrusted workloads at significant scale.
Building deep observability into the runtime: low‑level tracing, distributed profiling, and kernel‑adjacent debugging.
Working on high‑performance networking paths for routing, failover, and resilient cross‑region behaviour.
Extending multi‑cloud deployment tooling across major providers and customer VPCs using modern infrastructure‑as‑code.
Creating developer‑facing primitives that make browser / web automation reliable and ergonomic for AI and automation teams.
Contributing to and maintaining the open‑source components that sit at the core of the platform.
Tech environment
Infrastructure: modern container orchestration (e.g. Kubernetes/Nomad), microVM‑style virtualization, infrastructure‑as‑code, containers.
Backend: a mix of for cohesion, with Rust/Go used in performance‑critical paths, plus messaging, relational storage, and in‑memory datastores.
Frontend: TypeScript, React, and a modern build toolchain.
Observability & debugging: metrics dashboards, centralised logging, distributed tracing, eBPF‑style tooling, and kernel‑level visibility.
Heavy emphasis on Linux internals and systems performance; strong engineering culture around measurement and debugging.
What we're looking for
5+ years operating distributed systems in production, handling high request volumes and strict reliability requirements.
Deep Linux knowledge: you're comfortable with kernel‑level debugging, advanced tracing, and syscall‑level performance tuning.
Strong experience with resource isolation, multi‑tenancy, and security boundaries in real systems.
Solid networking fundamentals; you've debugged real packet‑level issues and latency problems in production environments.
Track record of shipping in high‑autonomy teams, owning projects end‑to‑end, and making pragmatic trade‑offs.
Strong signals (nice to have)
Hands‑on work with hypervisors or microVMs, or having built orchestration beyond "just using a managed cluster".
Contributions to kernels, virtualization, or core infrastructure projects (open source or internal).
Opinions on low‑level I/O and scheduling primitives informed by real production experience.
Background as a founder or early engineer at an infrastructure, devtools, or platform company.
Experience building developer‑facing infrastructure products or APIs.
Culture & setup
Very small, senior engineering team where everyone writes code, debugs production, and owns business‑critical systems.
Fast‑moving environment with periods of intensity around launches and incidents, typical of core infrastructure being relied on by customers.
High trust, high expectations, and high impact: your design and implementation decisions will directly shape how AI products in sectors like healthcare, supply chain, finance, and others interact with the web.
If you're an infrastructure engineer who enjoys working close to the metal and wants to help define the web automation layer for AI products, I'd be happy to share more and introduce you to the founders.
Sprachkenntnisse
- English
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