AI Engineer

Corridor; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading AI Security firm in San Francisco is seeking an AI Engineer to focus on building and experimenting with AI systems for code understanding and security. The role demands a strong engineering background, knowledge of machine learning, and hands-on experience with production-quality code. Applicants should have experience implementing end-to-end research ideas and collaborating on projects to enhance AI capabilities across the platform. This position offers opportunities for significant contributions in applied AI research and infrastructure development.

Qualifications

• 2+ years of industry or research experience in software engineering, ML, or a related field.
• Strong engineering background with experience building real systems or projects.
• Hands-on experience writing production-quality code (Python, ML frameworks, backend systems).

Responsibilities

• Build and experiment with AI systems for code understanding and vulnerability detection.
• Implement research ideas end-to-end, from prototypes to production-ready systems.
• Collaborate on applied research projects and contribute to publications or blog posts.

Skills

Software engineering

Machine learning

Production-quality code

Applied AI research

Model fine-tuning

Tools

Python

ML frameworks

Backend systems

Databases

Job description

Overview

AI has changed software development. Security hasn’t caught up — until now. Corridor is redefining product security for the AI era, giving developers the ability to secure their AI-generated code. Our team works at the intersection of AI and cybersecurity. Collectively, we’ve led security at some of the world’s largest companies, driven cybersecurity policy efforts in the US government, and worked on open models in government and academia. We’re hiring an AI Engineer to help build, experiment with, and ship the AI systems that power Corridor’s core product. This is a hands-on role combining applied research and engineering. You’ll work closely with the team to prototype ideas, turn research into production systems, and contribute to applied research at the intersection of AI and security.

What You’ll Do

• Build and experiment with AI systems for code understanding, vulnerability detection, and agentic security tools
• Implement research ideas end-to-end, from prototypes and benchmarks to production-ready systems
• Collaborate on applied research projects and contribute to publications, blog posts, or benchmarks
• Help design and maintain infrastructure for model evaluation, training, and experimentation
• Work closely with product and engineering teams to integrate AI capabilities into Corridor’s platform
• Stay current with new developments in AI, especially as they relate to code and security

What We’re Looking For

• Strong engineering background with experience building real systems or projects
• 2+ years of industry or research experience in software engineering, ML, or a related field
• Hands-on experience writing production-quality code (Python, ML frameworks, backend systems, vector stores, hybrid search, databases, etc.)
• Interest in applied AI research and the ability to turn ideas into working software
• Familiarity with model fine-tuning, evaluation pipelines, or RL-style environments
• Self-directed and curious. You can take ownership of ambiguous projects

Nice to Have

• Experience with code generation and/or security
• Prior research experience or publications in ML/AI or security venues
• Open-source contributions or public technical writing (blogs, benchmarks, demos)

About Us

• Co-founder and CEO Jack Cable is a top-ranked bug bounty hunter who previously led Secure by Design at CISA.
• Co-founder and CTO Ashwin Ramaswami built large-scale systems at Skiff, Caldera, and Nooks, and published research on AI and open foundation models at Stanford.
• CPO Alex Stamos is the former CISO of Facebook, Yahoo, and SentinelOne and a current lecturer at Stanford University.

Some of our angels and advisors include Russell Kaplan (Cognition), Thomas Wolf (Hugging Face), Jonathan Frankle (Databricks), and Mike Krieger (Anthropic).

Check out some of our existing blog posts on AI:

• The State of Secure Coding Benchmarks: BaxBench
• The State of Secure Coding Benchmarks: SecCodeBench