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Ebpf Linux Jobs in Missouri (NOW HIRING)

GenseeAI Inc.

Backend Engineer (Systems)

California, MO · On-site

$100 - $125/hr

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 ...

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Ebpf Linux information

What is an eBPF Linux engineer?

An eBPF Linux engineer is a software professional who specializes in working with eBPF (extended Berkeley Packet Filter) technology on the Linux operating system. eBPF allows for the execution of sandboxed programs in the Linux kernel, enabling advanced networking, security, and observability features without modifying kernel source code. Engineers in this role typically develop, optimize, and troubleshoot eBPF programs for use cases such as network monitoring, performance analysis, and security enforcement. They need a strong understanding of Linux internals, networking, and programming in C and sometimes Rust or Go. eBPF Linux engineers are increasingly in demand due to the growing use of cloud-native and containerized environments.

What are the key skills and qualifications needed to thrive as an eBPF Linux engineer?

To thrive as an eBPF Linux Engineer, you need strong skills in Linux systems programming, networking fundamentals, and proficiency with C or Go, often supported by a computer science degree or equivalent experience. Familiarity with eBPF tools (like bpftrace, libbpf, or bpftool), kernel debugging, and knowledge of containerization platforms are typically required. Analytical thinking, problem-solving, and effective collaboration set top professionals apart in this field. These competencies are crucial for developing efficient, secure, and scalable system observability or networking solutions within complex Linux environments.

What are some common challenges faced when developing with eBPF on Linux systems?

Developing with eBPF on Linux often involves navigating kernel version compatibility, as eBPF features evolve rapidly and may not be available on older kernels. Debugging eBPF programs can also be challenging due to strict verifier constraints and limited debugging tools. Additionally, integrating eBPF with existing monitoring or networking solutions requires a solid understanding of both kernel space and user space interactions. Collaborating with platform engineers and security teams is common, as eBPF programs frequently impact system performance and security.

What is the difference between Ebpf Linux vs Linux Kernel Developer?

AspectEbpf LinuxLinux Kernel Developer
Required credentialsKnowledge of eBPF, Linux internals, C programmingDeep understanding of Linux kernel, C, and kernel modules
Work environmentDeveloping and deploying eBPF programs within Linux systemsWriting, maintaining, and optimizing Linux kernel code
Employer and industry usageTech companies, cloud providers, security firms using eBPF for monitoring and securityOperating system vendors, enterprise IT, open-source projects

Ebpf Linux specialists focus on developing eBPF programs to enhance Linux system capabilities, while Linux Kernel Developers work on core kernel code. Both roles require strong C skills and Linux knowledge but differ in scope and focus.

What are popular job titles related to Ebpf Linux jobs in Missouri?

For Ebpf Linux jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Ebpf Linux jobs in Missouri look for?

The top searched job categories for Ebpf Linux jobs in Missouri are:

What cities in Missouri are hiring for Ebpf Linux jobs?

Cities in Missouri with the most Ebpf Linux job openings:

Ebpf Linux jobs near you
Infographic showing various Ebpf Linux job openings in Missouri as of July 2026, with employment types broken down into 86% Full Time, and 14% Contract. Highlights an 74% In-person, and 26% Remote job distribution.

Backend Engineer (Systems)

GenseeAI Inc.

California, MO • On-site

$100 - $125/hr

Other

Posted 20 days ago

Key responsibilities

  • Build and maintain low-level monitoring, sandboxing, and isolation systems to ensure AI agents operate safely.

  • Design and implement OS-level instrumentation, logging, telemetry, and detection logic for risky behavior.

  • Profile, optimize, and attribute system activity to specific agents, sessions, and tasks to ensure performance and accountability.

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.

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