Software Engineer - Security/Infrastructure

AfterQuery•San Francisco, CA

1d•$200,000 - $350,000•Onsite

About The Position

You’ll be responsible for protecting a system that handles highly sensitive workflows across AI training, expert networks, and enterprise integrations with leading model labs. This role is deeply technical. You’ll design and implement the infrastructure that keeps our systems resilient, rather than managing off-the-shelf security tools. We move fast and rely heavily on AI internally. You should be comfortable using LLMs to accelerate debugging, threat analysis, and system design—and just as comfortable replacing repetitive work with code. Security here isn’t isolated. When you’re not working on security problems, you’ll be building core systems—especially human-in-the-loop platforms and data infrastructure that power how frontier AI models are developed. We work in-person in San Francisco.

Requirements

You’ve built internal tools or systems to solve security problems—not just configured existing products
Strong programming ability in Python, Go, or TypeScript
Experience working with cloud environments (IAM, networking, containers)
Ability to identify vulnerabilities directly in code and system design
Experience creating or maintaining signal-based monitoring and alerting systems
Comfortable owning production issues when they arise
Able to move fluidly between security work and general engineering
2-7 years building software or security systems

Nice To Haves

Background in fast-scaling startups or high-output engineering teams
Exposure to AI systems, data pipelines, or model evaluation workflows
Familiarity with offensive security techniques
Experience building tools that other engineers depend on
Evidence of building and shipping systems from zero to production

Responsibilities

Build systems that identify and respond to real security events across our stack
Replace manual security workflows with programmatic, scalable solutions
Strengthen our cloud and production environments (GCP/AWS, containers, networking)
Design and enforce access control systems across internal teams, experts, and customers
Integrate security checks directly into development workflows without slowing shipping speed
Own incident handling systems and processes from detection through resolution
Secure surfaces unique to AI systems, including data flows and model interaction layers
Develop human-in-the-loop systems used in AI training and evaluation
Contribute to core infrastructure and internal tooling used across the company
Ship features across the stack that directly impact customers and model performance