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Bishop Fox

Offensive cybersecurity services and risk management

AI Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeUnited StatesNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or higher in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Cybersecurity, Information Security, or a closely related technical field.
  • A strong foundation in algorithms, data structures, and object-oriented programming.
  • Proficiency in Python, Java, C++, or a similar programming language.
  • Experience developing artificial intelligence or machine learning systems for security-related applications.
  • Experience with large language models and prompt engineering techniques.
  • Experience with artificial intelligence orchestration frameworks such as LangChain, LlamaIndex, AutoGen, or Semantic Kernel.
  • Experience implementing secure software development lifecycle 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 such as AWS, Azure, or GCP.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
  • Experience building RESTful APIs and microservices architectures.

Responsibilities

  • Architect and implement AI-powered systems for autonomous or semi-autonomous cybersecurity tasks, including vulnerability analysis, threat detection, alert triage, log analysis, and secure code review.
  • Design multi-agent architectures that orchestrate specialized AI agents, including vulnerability scanning, log analysis, and exploit pattern detection agents.
  • Develop retrieval-augmented generation pipelines for securely querying internal knowledge bases, threat intelligence feeds, CVE databases, and security documentation.
  • Use large language models to generate secure software components, scripts, detection logic, and test cases.
  • Review and refine AI-generated code for compliance with secure coding standards, including OWASP Top 10 and secure software development lifecycle practices.
  • Implement 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 workflows for cybersecurity use cases.
  • Develop evaluation metrics for AI accuracy in threat detection, vulnerability identification, and remediation recommendations.
  • 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 that integrate AI-powered security tools into enterprise platforms.
  • Architect scalable, fault-tolerant distributed systems for real-time security event processing.
  • Deploy AI-enabled services in secure cloud environments using containerization and orchestration technologies.
  • 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 against 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, including latency, false positive rates, and 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 turn threat intelligence and security requirements into scalable AI-enabled solutions.
  • Provide technical guidance on AI governance, responsible AI deployment, and secure AI lifecycle management.

Desired Qualifications

  • A 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.

About the Company

Bishop Fox

Offensive cybersecurity services and risk management

Bishop Fox helps organizations reduce cybersecurity risk by performing offensive security testing that mimics real-world attacks. Its Cosmos platform combines automated scanning with expert-led testing to continuously identify and remediate high-risk exposures on dynamic attack surfaces. Compared with others, it emphasizes hands-on, real-world attack simulations and ongoing remediation across services like Attack Surface Management, True Exposure Identification, and Continuous Attack Emulation. The company’s goal is to help clients stay ahead of threats by exposing and closing security gaps before attackers can exploit them.

Company size
201-500
Company stage
Series B
Total funding
$154M
Headquarters
Tempe, AZ
Founded
2005

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