Rust Engineer

Backend Engineer - AI SaaS Platform - Rust/ Python My client is a venture-backed AI SaaS company building real-time intelligence infrastructure that turns raw data streams into actionable insight. Their platform ingests high-volume data from distributed sources, processes it in real time, and surfaces insights that help customers act faster and reduce risk. They're a small, high-impact engineering team inside a rapidly scaling company, and this hire will help shape their engineering culture and technical foundations as they grow. The Role My client is looking for an engineer who pairs strong software skills with an ambitious, exploratory mindset. You'll design and build the distributed systems, storage infrastructure, and platform primitives underpinning their core product - working across stream processing, storage, API design, data pipelines, and service architecture, in a Rust stack with Python at the platform API boundaries. You'll build robust, well-abstracted systems built to scale with a growing customer base, with ambitions of petabyte-scale data storage. You'll own meaningful architectural decisions and reason through unfamiliar problem domains under real constraints. Core Skills Core technologies: Rust, with Python at some API boundaries. Kafka, PostgreSQL/TimescaleDB/PostGIS, gRPC/protobuf, and Kubernetes. (Candidates aren't expected to have experience with all of these, but adjacent understanding is important.)Systems thinking: comfortable designing and operating production systems under real constraints -zero-downtime migrations, complex tradeoff analysis, and pragmatic decision-making that keeps services reliable as requirements shift.Software craft: writes clean, well-structured code with good use of abstractions and interfaces; opinionated about code review process and culture.Reasoning under uncertainty: can pick up unfamiliar systems and make sound architectural calls without a complete picture.AI-assisted development: fluent with LLM-assisted workflows, confident steering AI tooling toward high-quality output, and knows which problems are better solved by humans.Collaboration: comfortable seeking out context independently and building features with limited top-down instruction; appetite for cross-team communication.