AI Software Engineer, Bishop Fox
Cyber threat prevention platform
Be an early applicant
Cyber threat prevention platform
201-500 employees
Be an early applicant
201-500 employees
Company mission
Bishop Fox's mission is to help businesses minimize their exposure to cyber threats by providing an offensive, forward defense cyber threat prevention platform.
Role
Who you are
- Bachelor’s degree or higher in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Cybersecurity, Information Security, or a closely related technical field
- Strong foundation in algorithms, data structures, and object-oriented programming
- Proficiency in programming languages such as Python, Java, C++, or similar
- Experience developing AI or machine learning systems for security-related applications
- Experience working with large language models (LLMs) and prompt engineering techniques
- Experience with AI orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar)
- Experience implementing secure software development lifecycle (SSDLC) practices
- Knowledge of cybersecurity concepts including vulnerability management, threat modeling, penetration testing, SIEM/SOAR platforms, and common attack vectors
- Experience deploying applications in cloud environments (AWS, Azure, or GCP)
- Familiarity with containerization and orchestration tools (Docker, Kubernetes)
- Experience building RESTful APIs and microservices architectures
Desirable
- Master’s degree in Computer Science, Artificial Intelligence, or Cybersecurity
- Experience designing AI systems for automated threat detection or exploit analysis
- Experience with reinforcement learning, fine-tuning, or model evaluation frameworks
- Experience integrating AI systems with cybersecurity tooling ecosystems
- Familiarity with NIST, ISO 27001, or similar security standards
What the job involves
- The Agentic AI Software Engineer – Cybersecurity Systems designs, develops, and deploys advanced AI-driven software solutions to enhance cybersecurity detection, response, analysis, and automation capabilities
- This role focuses on building and maintaining agent-based artificial intelligence systems capable of autonomously generating code, conducting security analyses, triaging alerts, identifying vulnerabilities, and recommending remediation strategies, with structured human oversight and validation
- The position requires the application of advanced knowledge in computer science, artificial intelligence, machine learning, secure software engineering, distributed systems, and cybersecurity principles
- The role involves complex system design, secure AI integration, and the development of enterprise-grade security automation platforms
- Architect and implement AI-powered systems that perform autonomous or semi-autonomous cybersecurity tasks, including vulnerability analysis, threat detection, alert triage, log analysis, and secure code review
- Design multi-agent architectures capable of orchestrating specialized AI agents (e.g., vulnerability scanning agents, log analysis agents, exploit pattern detection agents)
- Develop retrieval-augmented generation (RAG) pipelines to enable AI systems to securely query internal knowledge bases, threat intelligence feeds, CVE databases, and security documentation
- Utilize large language models (LLMs) to generate secure software components, scripts, detection logic, and test cases
- Review and refine AI-generated code to ensure compliance with secure coding standards (e.g., OWASP Top 10, secure SDLC practices)
- Implement automated guardrails to detect insecure outputs, prompt injection vulnerabilities, model hallucinations, and data leakage risks
- Design validation frameworks to benchmark AI-generated security outputs against known vulnerability patterns
- Design and implement reinforcement learning from human feedback (RLHF) workflows for cybersecurity use cases
- Develop evaluation metrics for AI accuracy in threat detection, vulnerability identification, and remediation recommendations
- Continuously refine prompt engineering strategies, model tuning parameters, and system architecture to improve security reliability and precision
- Implement explainability mechanisms to support auditability and defensibility of AI-driven security decisions
- Develop and maintain APIs and microservices to integrate AI-powered security tools into enterprise platforms
- Architect scalable and fault-tolerant distributed systems to support real-time security event processing
- Deploy AI-enabled services within secure cloud environments (e.g., AWS, Azure, GCP) using containerization and orchestration technologies (Docker, Kubernetes)
- Integrate AI systems with SIEM, SOAR, vulnerability management, and endpoint detection platforms
- Conduct threat modeling for AI systems to identify adversarial risks, model exploitation vectors, and prompt injection vulnerabilities
- Implement secure authentication, authorization, encryption, and data governance controls
- Develop safeguards to prevent misuse of AI systems in exploit development or unintended security bypass scenarios
- Perform security reviews and penetration testing of AI-driven software components
- Design automated test pipelines for AI-driven security workflows
- Conduct adversarial testing to evaluate resilience against malicious inputs
- Monitor system performance metrics (latency, false positive rates, detection accuracy)
- Optimize inference pipelines and distributed systems for reliability and scalability
- Produce detailed architectural documentation for AI security systems
- Collaborate with cybersecurity researchers, product teams, software engineers, and cloud architects to translate threat intelligence and security requirements into scalable AI-enabled solutions
- Provide technical guidance on AI governance, responsible AI deployment, and secure AI lifecycle management
Our take
Cybersecurity software is used by many businesses across the world to mitigate their cyber risk, yet breaches are still common. A prime reason for this is the lack of visibility businesses have into the roots of their IT and data stacks, making it difficult to truly understand and prevent future attacks.
Bishop Fox sets itself apart through its offensive cyber threat prevention platform which is focused on applying a "forward defense" approach (with risk visibility and prevention instead of reaction). The company achieves this by mapping IT stacks to facilitate real-time visibility of attack perimeters, applying complex real-world cyber threat scenarios to assess resilience, and conducting continuous attack emulations.
The attack surface management category has grown in importance in recent years, especially for software. As a result, the market has become increasingly crowded. Bishop Fox has, however, raised impressive funding, which is being used to grow its team and expand its product offering in order to further set itself apart.
Freddie
Company Specialist at Welcome to the Jungle
Insights
0% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Nov 2022
$54m
SERIES B
Jul 2022
$75m
SERIES B
Total funding: $154m
Company benefits
- Full medical, dental, and vision
- Paid vacations and holidays
- Phone plan
- Commuter benefits program
- Maternity and paternity leave
- Training budgets. Cool swag. Stocked fridges
- Remote-first
Company HQ
Tempe, AZ
Leadership
Vinnie Liu
(Co-Founder & CEO)Experience as Information Security Specialist for Honeywell International. Advisory Board Member of University of Advancing Technology since 2012.
Francis Brown
(Co-Founder & Board Director)Was a security Consultant for Advanced Security Centers, and has experience as IT Security Specialist for Honeywell International.
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