Member of Technical Staff
Job description
About the role
SII researchers evaluate real-world risks to AI-native products and convert findings into protections for users. The role translates security research into safeguards for systems used by millions. Researchers interrogate the threat model of AI driven products and surface subtle attack vectors before they reach production. They own the end to end security narrative from hypothesis to mitigated risk. The work demands rigor in experimentation and clarity in storytelling to bridge security and product teams. Findings are not just academic; they become shipped controls that change how users interact with the product. This role sits at the intersection of adversarial thinking and engineering pragmatism.
Key facts
What you'll do
Analysis informs product teams about user risks and guides secure design.
Findings translate operational realities into prioritized mitigations that protect users and platforms.
Analyze adversarial tactics in deployed environments and design controls to reduce risks to acceptable levels.
Measurement supports objective comparison of techniques and guides iterative improvements.
Collaboration integrates research findings at scale into production workflows.
Engagement with external partners broadens the scope and impact of security research initiatives.
Publication advances collective knowledge and supports responsible disclosure practices.
Design and run red team exercises focused on AI native workflows to uncover systemic weaknesses.
Evaluate supply chain risks in third party models and data pipelines to ensure robust provenance.
Create threat models and attack simulations that map onto product feature roadmaps.
Partner with engineers to define secure by design requirements and verify implementation correctness.
Translate complex attack narratives into clear, actionable insights for engineering and leadership.
Requirements
Hold a PhD (or equivalent research experience) in Computer Science, Computer Engineering, or a related field, with a primary focus on security and/or privacy. Equivalent research experience may substitute for formal doctoral training when justified.
Demonstrate original, impactful research through publications at top security conferences (IEEE S&P, USENIX Security, ACM CCS, NDSS). A publication record validates sustained ability to produce high quality, influential work.
Show deep expertise in security of agentic systems, systems security, web and applications security, program analysis, and software security. Expertise aligns with the specific threat landscape of AI driven products.
Write Python code and experiment with implementations, with optional experience in TypeScript, Go, and/or Rust.
Operate with high independence, take ownership, and thrive in a fast-paced environment where research directly informs product.
Travel is not mentioned as a requirement; the role is based in San Francisco.
Translate complex attack narratives into clear, actionable insights for engineering and leadership. Clear and concise communication ensures stakeholders can act on security risks and prioritize mitigations.
Practical notes
The role is based in San Francisco and requires compliance with any applicable visa, citizenship, or clearance rules as defined by law. Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
The role centers on computer security research and systems security for AI products. Core tools include Python and languages such as TypeScript, Go, and Rust. Success depends on publishing at top security conferences and collaborating with an internal research team.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.