Backend Engineer (Systems)

GenseeAI Inc.; California (MO); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Competitive compensation in cash + equity

Ownership over projects

Direct influence on architecture and product direction

Job summary

GenseeAI Inc. in California seeks a backend engineer to build systems that ensure AI agent safety. Responsibilities include developing monitoring and isolation systems, and direct collaboration with company founders on architecture and roadmap.

The ideal candidate has a Bachelor's degree in Computer Science and experience in backend or systems engineering. Strong systems fundamentals and knowledge of languages like Rust or Go are essential for success in this high-ownership role.

Qualifications

• 1+ years of professional backend or systems engineering experience.
• Strong systems fundamentals including processes, file systems, and memory.
• Experience with high-throughput data pipelines and observability.

Responsibilities

• Build performant and low-level monitoring of system activity.
• Design and implement sandboxing to contain agent abilities.
• Work directly with founders on architecture decisions.

Skills

Backend development

Systems engineering

Linux internals

Concurrency

Anomaly detection

Education

Bachelor's degree in Computer Science or equivalent

Tools

Rust

Go

C/C++

Python

Job description

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.