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Encord

AI-native data infrastructure for Physical AI

Senior Security Engineer - Application Security

Security Engineering & ArchitecturePosted on Nov 12
Full-timeLondon, UK

About the Job

Requirements

  • At least 7 years of experience in software or security engineering, including significant hands-on application security experience.
  • Strong coding ability in Python and/or TypeScript, with the ability to review and fix code.
  • Deep knowledge of web and API security, including OWASP Top 10, OAuth/OIDC, authorization models, SSRF, injection, and deserialisation.
  • Experience securing cloud-native SaaS using GCP or AWS, Kubernetes, and containers.
  • A track record of building security tooling and processes in a fast-moving product company.

Responsibilities

  • Own the application security program end to end, including threat modelling, secure design reviews, code review, and vulnerability management.
  • Build security into the SDLC by integrating SAST, DAST, dependency/SCA, and secrets scanning into CI/CD without slowing teams down.
  • Partner with engineering on authentication, authorization, multi-tenancy isolation, and data protection across APIs and SDKs.
  • Lead penetration testing, bug bounty triage, and incident response for application-layer issues.
  • Support customer security reviews and compliance with SOC 2, HIPAA, and GDPR through practical technical controls.
  • Mentor engineers and raise security standards across the organisation.

Desired Qualifications

  • Experience with ML/AI systems security, including data pipelines, model supply chain, and LLM-specific risks such as prompt injection.
  • Background in regulated industries such as healthcare.
  • Previous experience as an early or first dedicated security hire.

About the Company

Encord

AI-native data infrastructure for Physical AI

Encord provides an AI-native data infrastructure platform for Physical AI, helping enterprises manage multimodal data for robotics, autonomous systems, and related applications. It offers Encord Annotate for collaborative multimodal annotation, Encord Active for data curation and quality evaluation, and Encord Index for petabyte-scale dataset search and management, covering the full data lifecycle from collection to deployment. The platform acts as a universal data layer for production-grade Physical AI, addressing the infrastructure gap left by cloud-era tools focused on text and tabular data and emphasizing multimodal data and embodied AI. Its goal is to enable teams to build, evaluate, and deploy real-world AI systems more efficiently with scalable, reliable data tooling.

Company size
201-500
Company stage
Series C
Total funding
$107.1M
Headquarters
London, United Kingdom
Founded
2020

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