Cohere
Software Engineer, Security Agents
United States · Senior · Full-time
Sponsorship not specifiedDetected 32 days ago
PythonFull-Stack DevelopmentCode ReviewMachine LearningAgentic AIAI OrchestrationCybersecurityResearchCommunication
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About the role
- Ready to build AI agents that revolutionize enterprise security?
- The North Security team is looking for a Senior Software Engineer to create autonomous systems that handle the complex, critical tasks security practitioners face every day.
Responsibilities
- Build autonomous security agents that perform alert triage, secure code reviews, threat modeling, and vulnerability assessment
- Develop agent orchestration systems that help security practitioners automate repetitive security tasks
- Design and implement agent security controls to ensure our AI agents can safely interact with sensitive enterprise data
- Create the security infrastructure that allows agents to operate in high-trust environments with stringent deployment requirements
- Research and implement novel security patterns for AI agent systems, sometimes requiring custom solutions where standard libraries fall short
- Conduct security testing of both the agents you build and the platform that runs them.
- As a Senior Software Engineer focused on agentic security, you'll build intelligent systems that empower security teams.
- We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
- We're training and deploying frontier models for enterprises who are building AI systems.
- We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities.
Requirements
- 5+ years of software engineering experience with a track record of shipping user-facing security features
- Strong Python development skills with significant production experience
- Ability to think about security at multiple layers: application security, agent behavior security, and infrastructure security
- Thrive in fast-paced environments where you can adapt to evolving priorities
- Experience building or working with autonomous systems, AI agents, or intelligent automation
- Solid understanding of security principles including session management, authentication, authorization, and secure coding practices
- Comfortable working across the full stack and diving into unfamiliar codebases to understand and fix issues
- Excited about the intersection of AI/ML and security engineering.
- This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
Compensation
- Annual enrichment
Benefits
- 6 weeks of paid vacation (30 working days!)
- Everyone receives a $500 home office stipend to set up your workspace properly.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
- Education & learning stipend for conferences, courses, and coaching.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
Company info
- We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
- We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul.
- Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process.
This listing is sourced directly from Cohere's careers page and normalized into a canonical job model.