Member of Technical Staff - Security Engineer
Reflection4 months ago
Responsibilities
- Contribute engineering work to security projects including agentic AI incident detection and response and internal AI agents.
- Implement security controls for AI agents, including sandboxes, identity, and authorization systems.
- Define software supply chain security strategy, tooling, and infrastructure, including SCA and SBOM analysis.
- Deploy controls to rapidly ingest and respond to emerging supply chain attacks.
- Develop and maintain a comprehensive threat model for the software stack.
- Drive the penetration testing program using threat-model-based prioritization.
- Define and promote secure coding practices and architecture patterns for AI/ML systems.
- Integrate SAST tools into CI/CD pipelines for continuous vulnerability analysis.
- Define and implement a comprehensive Secure Software Development Lifecycle.
Requirements
- Strong proficiency with Python or Golang.
- A track record of architecting and building complex software systems.
- Familiarity with common application logic exploit vectors.
- Experience implementing and rolling out cross-functional projects affecting many teams.
- An AI-native engineering workflow.
- Experience working with Kubernetes.
- Experience working with AWS and/or GCP.
- Interest in developing across infrastructure security, incident detection and response, and digital forensics.
- Willingness to contribute to cross-functional projects across multiple security pillars.
- Experience building programs from 0 to 1.
Benefits
- Top-tier compensation with salary and equity.
- Comprehensive medical, dental, vision, life, and disability insurance.
- Fully paid parental leave for all new parents, including adoptive and surrogate journeys.
- Financial support for family planning.
- Paid time off and relocation support.
- Lunch and dinner provided daily, plus regular off-sites and team celebrations.
Categories
About Reflection
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. Our team previously built frontier LLMs at labs like DeepMind, OpenAI, and Anthropic. We believe AI should be built in the open, with transparent research and collaborative development. That means giving enterprises, governments, and sovereign entities true ownership and control of AI that performs at the highest level. Our mission: make intelligence open and accessible to all.