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Backend Engineer (Systems)GenseeAI Inc. • California, Maryland, United States
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Backend Engineer (Systems)

GenseeAI Inc.
  • US
    California, Maryland, United States
  • US
    California, Maryland, United States
Jetzt Bewerben

Über

We are looking for a strong backend engineer who loves working close to the metal. You'll build the systems layer that makes AI agents safe to run — low-level monitoring, isolation, and detection that watch how agents behave and constrain what they can do. This is a high-ownership role with the chance to shape both technical architecture and product direction from an early stage.
What you will likely work on:
Build performant, low-level monitoring of process, file, and network activity
Design and implement sandboxing and isolation that contain what an agent can do without blocking legitimate work
Build OS-level instrumentation (e.g., eBPF) and the userspace pipeline that normalizes and enriches events
Build the logging, telemetry, and storage path: high-throughput, low-overhead, privacy-by-default
Build detection and prevention logic for risky behavior — deterministic rules first, with lightweight ML for anomaly detection where it earns its place
Attribute observed system activity back to the responsible agent, session, and task
Profile and optimize relentlessly to keep overhead invisible on a user's machine
Work directly with founders on architecture, roadmap, and prioritization
Qualifications:
Bachelor's degree in Computer Science or a related field, or equivalent practical experience. Master's degree or equivalent industry experience is preferred.
1+ years of professional backend or systems engineering experience.
Strong systems fundamentals — processes, file systems, syscalls, memory, and concurrency
Comfortable working close to the operating system, in a systems language
Have experience with some mix of:
A systems language — Rust, Go, or C/C++ — plus Python
Linux internals and the kernel/userspace boundary
eBPF, sandboxing, or other OS-level instrumentation and isolation
High-throughput data pipelines, logging, and observability
Applied ML for detection, anomaly detection, or classification
Understand how to build systems that scale and fail gracefully
Are strong with AI-assisted coding, but do not trust generated code blindly and can manually inspect and debug it carefully
Communicate clearly and can work well with both teammates and users
Enjoy ownership, ambiguity, and moving quickly
Nice to have:
macOS systems internals — a big plus
Rust experience (a strong plus — much of our systems work is in Rust)
Familiarity with eBPF, seccomp, AppArmor, SELinux, or related technologies
Experience with EDR, endpoint, or process/behavioral monitoring
Applied ML for security — anomaly detection, sequence models, or classification
Interest in AI agent safety and the emerging agent threat landscape
Experience debugging production incidents and improving observability
Prior startup experience
Work on hard infrastructure and product problems that matter across the entire AI agent ecosystem
Build from the ground up with direct influence on architecture and product direction
Own real systems end-to-end, not just tickets in a queue
Work closely with the founders every day
Competitive compensation in cash + equity
Candidates must already have authorization to work in the US, or authorization to work in the country where they live. We do not sponsor H-1B visas.
Start As soon as possible.
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  • California, Maryland, United States

Sprachkenntnisse

  • English
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