Join a small founding engineering team building security infrastructure for enterprise AI systems. You will help create the platform's data and detection capabilities, working directly with customers to ship practical protections against emerging risks from AI agents and models.
Own features from design through production release, delivering solutions to enterprise customers on short timelines.
Build data pipelines that process high-volume telemetry from endpoint, network, identity, and model gateway systems.
Design real-time detection and policy enforcement for emerging AI agent failure modes.
Work with customers during proofs of concept and deployments, adapting and shipping features as needs arise.
Train or tune small models to make low-latency decisions based on behavioral baselines.
Red-team models and agents to uncover issues such as prompt injection, tool misuse, data exposure, and scope drift.
Help shape the platform architecture and technical direction.
Zero to five years of software engineering experience, including internships, with a hands-on individual contributor focus.
Strong backend and full-stack engineering skills, with solid fundamentals in distributed systems, infrastructure, or large-scale data processing.
Experience shipping production systems and working effectively with limited process and support.
Familiarity with Go or Rust, streaming pipelines, real-time data infrastructure, cloud infrastructure, or security integrations.
Interest or experience in applied machine learning, model fine-tuning, security engineering, adversarial testing, or customer-facing engineering.
Strong computer science fundamentals; experience in competitive programming or quantitative engineering is also relevant.
Annual salary range: $160,000 to $300,000 USD. Visa sponsorship is available.
On-site in San Francisco, California, United States.
Job details are sourced from the employer's original posting.
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