Software Engineer, Security

Thinking Machines Lab•San Francisco, CA

About The Position

Thinking Machines is hiring a software engineer focused on making its products secure by default while supporting fast product iteration. The engineer will work with product and research teams to incorporate security into product design and development and build tooling and automation that keep systems safe at scale. The role is based in San Francisco, California.

Requirements

Bachelor’s degree or equivalent experience in computer science, engineering, or a similar field.
Proficiency in at least one backend language; the company uses Python or Rust.
Strong generalist software engineering background and ability to review production code for security risks.
Hands-on experience securing web applications and APIs, especially authentication flows, access control, secrets management, input validation, and data protection.
Familiarity with common vulnerability classes and prevention frameworks, and experience hardening prototypes into production.
Comfort with modern cloud infrastructure and understanding how application concerns intersect with infrastructure.
Comfort operating across the stack and owning projects end-to-end.
Ability to thrive in a highly collaborative environment with cross-functional partners and subject matter experts.
Bias for action and initiative to work across stacks and teams to help deliver improvements.

Nice To Haves

Experience securing AI-powered products or working with ML/LLM APIs and their unique threat models.
Background in human-computer interaction, especially where security or trust plays a central role in the user experience.
Strong skills in rapid prototyping and iteration, with a habit of turning ad-hoc fixes into reusable patterns and tools.
Open-source security work, bug bounty write-ups, or published tooling.

Responsibilities

Partner with product and research teams to embed security into the development lifecycle through threat modeling, design reviews, and secure defaults for new features.
Design and implement security controls across the product stack, including authentication, authorization, session management, and input validation.
Build and maintain security tooling and automation for engineers, including secure frameworks and templates, CI/CD checks, dependency management, and vulnerability detection.
Collaborate with researchers to identify and mitigate AI-specific product risks, such as model abuse, prompt injection, data leakage, and misuse of capabilities.
Improve observability and detection for security-relevant events, including access anomalies, abuse patterns, and suspicious production behavior.