Backend Engineer (Systems)

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

Why join

• 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

Work authorization

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.

About GenseeAI:

GenseeAI is a research-based, quickly growing startup building the foundational infrastructure layer for the future of AI agents. Instead of building another agent, we focus on the harder and more important layer underneath: making agents execute with far better efficiency, safety, security, and privacy in real production environments. GenseeAI is founded by a UCSD professor and an ex-Googler (L7) who spent 10+ years managing core ML/AI infrastructure at Google. If you join now, you won’t just be joining a startup — you’ll be helping build a piece of the stack that could become essential to the entire AI agent ecosystem.