Software Engineer, Security

Posted 13 Days Ago
San Francisco, CA, USA
In-Office
300K-350K Annually
Entry level
Artificial Intelligence • Information Technology
The Role
Build security into products and development workflows through threat modeling, secure design reviews, authentication and authorization controls, security tooling, CI/CD checks, vulnerability detection, and observability. Secure web applications and APIs, collaborate with AI researchers on risks such as prompt injection and data leakage, and improve detection of abuse and suspicious production behavior. The role requires backend software engineering, cloud infrastructure knowledge, and end-to-end project ownership.
Summary Generated by Built In
About Thinking Machines

The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and crafting interfaces that broaden human-AI communication. We believe the future worth building is human, and we're hiring people who want to build it.

About the Role

We’re looking for a software engineer focused on making our products secure by default while supporting fast and ambitious product iteration. You’ll embed with product and research teams to bake security into design and development and to build tooling and automation that keep systems safe at scale.

What You’ll Do
  • Partner with product and research teams to embed security into the development lifecycle: threat modeling, design reviews, and secure defaults for new features.

  • Design and implement security controls across our product stack (authentication, authorization, session management, input validation, etc.).

  • Build and maintain security tooling and automation for engineers: 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, or misuse of capabilities.

  • Improve observability and detection for security-relevant events: access anomalies, abuse patterns, and suspicious behavior in production.

Skills and Qualifications

Minimum qualifications:

  • Bachelor’s degree or equivalent experience in computer science, engineering, or similar.

  • Proficiency in at least one backend language (we use Python or Rust).

  • Strong generalist software engineering background and ability to review production code for security risks.

  • Hands-on experience securing web apps and APIs especially auth flows, access control, secrets management, input validation, and data protection.

  • Familiarity with common vulnerability classes and prevention frameworks; 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.

  • Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.

  • A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications — we encourage you to apply if you meet some but not all of these:

  • 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.

Logistics
  • Location: This role is based in San Francisco, California. 

  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $300,000 - $350,000 USD.

  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.

  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

Skills Required

  • Bachelor's degree or equivalent experience in computer science, engineering, or a similar field
  • Proficiency in at least one backend language, specifically 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, including authentication, access control, secrets management, input validation, and data protection
  • Familiarity with common vulnerability classes and prevention frameworks
  • Experience hardening prototypes into production
  • Understanding of modern cloud infrastructure and how application concerns intersect with infrastructure
  • Ability to operate across the stack and own projects end-to-end
  • Ability to work collaboratively with cross-functional partners and subject matter experts
  • Initiative to work across different stacks and teams to deliver projects
  • Experience securing AI-powered products or working with ML/LLM APIs and their unique threat models
  • Background in human-computer interaction involving security or trust in user experience
  • Strong rapid prototyping and iteration skills, including converting ad hoc fixes into reusable patterns and tools
  • Open-source security work, bug bounty write-ups, or published tooling
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The Company
HQ: Singapore
91 Employees

What We Do

Thinking Machines Lab is an artificial intelligence research and product company. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. While AI capabilities have advanced dramatically, key gaps remain. The scientific community's understanding of frontier AI systems lags behind rapidly advancing capabilities. Knowledge of how these systems are trained is concentrated within the top research labs, limiting both the public discourse on AI and people's abilities to use AI effectively. And, despite their potential, these systems remain difficult for people to customize to their specific needs and values. To bridge the gaps, we're building Thinking Machines Lab to make AI systems more widely understood, customizable and generally capable. We are scientists, engineers, and builders who've created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.

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