What You Will Do
1. Design and Develop Agentic AI Systems for Cybersecurity
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.
2. AI-Assisted Secure Code Generation & Review
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.
3. Human-in-the-Loop AI Governance & Model Optimization
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.
4. Secure System Architecture & Integration
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.
5. Security Engineering & Threat Modeling
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.
6. Testing, Validation & Performance Optimization
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.
7. Documentation & Cross-Functional Collaboration
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.
Your Experience
Required Education
Bachelor’s degree or higher in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Cybersecurity, Information Security, or a closely related technical field.
Required Experience & Technical Skills
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.
Preferred Qualifications
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.
Our Values
We strive to live by our values every day, in support of our core tenets, which are to deliver the highest quality of work for our clients, quality of life for our team, and quality of business for our industry and our future.
Be Excellent to Each Other
Do the Right Thing
Do What You’ll Say You’ll Do
Get Better Together
Give a Sh*t
We offer a variety of benefits and perks, such as
Generous Time Off and Company-Wide Holidays
Health Insurance options including Medical, Dental, Vision
Retirement; 401k matching for Traditional and Roth accounts in the US
Work From Home Support
Monthly allowance for cell phone and internet
Training Budget
Paid Parental Leave
Specialty Occupation Justification
The duties of this position require the theoretical and practical application of specialized knowledge in computer science, artificial intelligence, distributed systems, and cybersecurity engineering. The design and implementation of AI-driven, agent-based cybersecurity systems necessitate advanced understanding of algorithms, machine learning methodologies, secure system architecture, threat modeling, and secure coding standards. Such knowledge is typically acquired through completion of at least a bachelor’s degree in a specific technical field such as Computer Science, Artificial Intelligence, or Cybersecurity.
The complexity of developing autonomous AI systems that analyze vulnerabilities, evaluate exploit patterns, and integrate securely with enterprise cybersecurity infrastructure requires a highly specialized educational background and cannot be performed without advanced technical training.
Bishop Fox is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex including sexual orientation and gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. All new hires must pass a background check as a condition of employment.
