Senior Security Engineer

LangChain LangChain · Data AI · San Francisco, CA · Engineering

LangChain is seeking a Senior Security Engineer to secure its AI agent platform, focusing on application and infrastructure security for their SDK, LangSmith, and LangGraph services. The role involves owning product security, implementing secure authentication and authorization, managing vulnerabilities, shipping secure code, and hardening infrastructure. Experience with cloud security, application security, and supply-chain security is required, with a preference for AI tooling familiarity and understanding of AI threats.

What you'd actually do

  1. Own product & platform security: Design and drive application/infrastructure security controls across LangSmith, LangGraph, and the LangChain SDK ecosystem (Python/TS/Go).
  2. Secure-by-default authN/Z: Evolve SSO/SAML/OIDC/SCIM, token lifecycles, service‑to‑service auth, and tenant isolation for cloud and self‑hosted customers.
  3. Vuln management: Own scanning/triage/patch SLAs; coordinate with engineering to remediate quickly without slowing delivery.
  4. Ship code, reviews, and tooling: Land secure designs, write PRs, perform penetration testing, and introduce lightweight checks (linters, dependency/supply‑chain scanning, SBOM/SLSA provenance) to enable security at scale.
  5. Hardening & operations: Network segmentation/Zero Trust, Kubernetes posture, secrets management, key rotation, least‑privilege IAM, egress controls

Skills

Required

  • 5+ years in security engineering
  • strong software skills (Python or Go; TypeScript a plus)
  • Depth in cloud/Kubernetes security (e.g., GCP/AWS IAM, workload identity, admission controls, network policies)
  • Hands-on AppSec: code review, threat modeling, secure design, secrets & key management, authn/z patterns, multi‑tenant isolation
  • Experience building detection & response and running incident management
  • Familiarity with supply‑chain security (SBOM, sigstore/cosign, SLSA‑style controls) and dependency risk management
  • Clear, pragmatic communication with engineers and customers

Nice to have

  • Security for SaaS + self-hosted offerings, including air‑gapped deployments
  • Proficiency with AI tooling to expedite security reviews
  • Solid understanding of AI itself, including AI threats, adversarial testing
  • Exposure to SOC 2 / ISO 27001 programs and evidence automation
  • Experience with Go services and Infra as Code (Terraform/Helm), plus policy‑as‑code (OPA/Gatekeeper/Kyverno)
  • Knowledge of privacy patterns (data minimization, retention, masking, workspace scoping)

What the JD emphasized

  • security roadmap
  • immediate hardening wins
  • raise the bar on how AI infra is protected
  • application security
  • cloud/infrastructure security
  • secure design
  • secure design
  • secure design