Braintrust

Detection and Response Engineer

Braintrust
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14 days ago
Seattle, WA, USA +2 moreSenior
H1B sponsor

Responsibilities

  • Build security telemetry pipelines across ECS/Kubernetes, CI/CD systems, identity systems, endpoints, and agentic workloads.
  • Continuously improve detections for attacks, abuse, and anomalous behavior while owning the alert pipeline and maintaining high signal-to-noise.
  • Lead incident response and participate in on-call by triaging, scoping, containing, and remediating incidents, followed by postmortems.
  • Proactively hunt for threats and build tooling that converts evidence into new detections.
  • Build agents that triage alerts, enrich findings, gather evidence, and scope incidents with human-in-the-loop controls and evaluations.
  • Run vulnerability response by evaluating impact and driving remediation across infrastructure.

Requirements

  • Proficiency with modern backend technologies and the ability to write production code in Python, TypeScript, or Go.
  • AWS experience with IAM, VPC, KMS, GuardDuty, and CloudTrail, plus working fluency in Azure or GCP.
  • Kubernetes detection experience involving audit logs, runtime telemetry, and workload identity.
  • Knowledge of endpoint security on macOS and detection and response techniques.
  • Hands-on incident experience, including on-call participation, incident leadership, and postmortem writing.
  • A clear point of view on AI/LLM security and hands-on experience defending relevant threats.
  • Strong written and verbal communication.
  • Prior experience with LLM red-teaming, agent sandbox research, or other AI-relevant security threat defense is a bonus.

Benefits

  • Medical, dental, and vision insurance.
  • Daily lunch, snacks, and beverages.
  • Flexible time off.
  • Competitive salary and equity.
  • WiFi and cellphone stipend.
Braintrust

About Braintrust

201-500 employees

Braintrust builds an AI observability and evaluation platform for teams deploying LLM-powered applications. It unifies evals and production monitoring to compare models, test prompts, catch regressions, and turn real usage data into better releases; it can be self-hosted or used as a managed service. Customers include Notion, Stripe, Zapier, Vercel, and Ramp, and the software is sold by subscription to engineering and data teams.

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