{"id":132416,"url":"https://alion.io/job/bishop-fox-ai-software-engineer","title":"AI Software Engineer","company":{"id":34929,"name":"Bishop Fox","domain":"bishopfox.com","url":"https://alion.io/company/bishop-fox","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":156000,"max_usd":343000,"period":"year","method":"role_country_seniority_unknown","sample_n":4027},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"CVE","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OWASP Top 10","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Red Teaming","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"SIEM","optional":false},{"name":"Threat Modeling","optional":false},{"name":"Fine-tuning","optional":true},{"name":"ISO 27001","optional":true}],"status":"live","first_seen_at":"2026-02-18T18:42:39Z","employer_posted_date":"2026-07-31","last_verified_at":"2026-10-16T18:42:27Z","board_verified":true,"closed_at":null,"days_open":240,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":239},"description":"Bishop Fox is the leading authority in offensive security, providing solutions ranging from continuous penetration testing, red teaming, and attack surface management to product, cloud, and application security assessments. We’ve worked with more than a quarter of the Fortune 100, half of the Fortune 10, eight of the top 10 global technology companies, and all of the top global media companies. Our managed service platform, service innovation, and culture of excellence continue to gather accolades from industry award programs including Fast Company, Inc., SC Media, and others. For more than 16 years, we've been contributing and giving back to the security community. We’ve published more than 16 open source tools and 50 security advisories in the last five years alone. Learn more at bishopfox.com or follow us on social media.\nWho You Are \nThe 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. \nThe 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. \nWhat You Will Do \n1. Design and Develop Agentic AI Systems for Cybersecurity \nArchitect 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.\nDesign multi-agent architectures capable of orchestrating specialized AI agents (e.g., vulnerability scanning agents, log analysis agents, exploit pattern detection agents).\nDevelop retrieval-augmented generation (RAG) pipelines to enable AI systems to securely query internal knowledge bases, threat intelligence feeds, CVE databases, and security documentation. \n2. AI-Assisted Secure Code Generation & Review \nUtilize large language models (LLMs) to generate secure software components, scripts, detection logic, and test cases.\nReview and refine AI-generated code to ensure compliance with secure coding standards (e.g., OWASP Top 10, secure SDLC practices).\nImplement automated guardrails to detect insecure outputs, prompt injection vulnerabilities, model hallucinations, and data leakage risks.\nDesign validation frameworks to benchmark AI-generated security outputs against known vulnerability patterns. \n3. Human-in-the-Loop AI Governance & Model Optimization \nDesign and implement reinforcement learning from human feedback (RLHF) workflows for cybersecurity use cases.\nDevelop evaluation metrics for AI accuracy in threat detection, vulnerability identification, and remediation recommendations.\nContinuously refine prompt engineering strategies, model tuning parameters, and system architecture to improve security reliability and precision.\nImplement explainability mechanisms to support auditability and defensibility of AI-driven security decisions. \n4. Secure System Architecture & Integration \nDevelop and maintain APIs and microservices to integrate AI-powered security tools into enterprise platforms.\nArchitect scalable and fault-tolerant distributed systems to support real-time security event processing.\nDeploy AI-enabled services within secure cloud environments (e.g., AWS, Azure, GCP) using containerization and orchestration technologies (Docker, Kubernetes).\nIntegrate AI systems with SIEM, SOAR, vulnerability management, and endpoint detection platforms. \n5. Security Engineering & Threat Modeling \nConduct threat modeling for AI systems to identify adversarial risks, model exploitation vectors, and prompt injection vulnerabilities.\nImplement secure authentication, authorization, encryption, and data governance controls.\nDevelop safeguards to prevent misuse of AI systems in exploit development or unintended security bypass scenarios.\nPerform security reviews and penetration testing of AI-driven software components. \n6. Testing, Validation & Performance Optimization \nDesign automated test pipelines for AI-driven security workflows.\nConduct adversarial testing to evaluate resilience against malicious inputs.\nMonitor system performance metrics (latency, false positive rates, detection accuracy).\nOptimize inference pipelines and distributed systems for reliability and scalability. \n7. Documentation & Cross-Functional Collaboration \nProduce detailed architectural documentation for AI security systems.\nCollaborate with cybersecurity researchers, product teams, software engineers, and cloud architects to translate threat intelligence and security requirements into scalable AI-enabled solutions.\nProvide technical guidance on AI governance, responsible AI deployment, and secure AI lifecycle management. \nYour Experience \nRequired EducationBachelor’s degree or higher in Computer Science, Computer Engineering, Software Engineering, Artificial Intelligence, Cybersecurity, Information Security, or a closely related technical field.\n\nRequired Experience & Technical SkillsStrong foundation in algorithms, data structures, and object-oriented programming.\nProficiency in programming languages such as Python, Java, C++, or similar.\nExperience developing AI or machine learning systems for security-related applications.\nExperience working with large language models (LLMs) and prompt engineering techniques.\nExperience with AI orchestration frameworks (e.g., LangChain, LlamaIndex, AutoGen, Semantic Kernel, or similar).\nExperience implementing secure software development lifecycle (SSDLC) practices.\nKnowledge of cybersecurity concepts including vulnerability management, threat modeling, penetration testing, SIEM/SOAR platforms, and common attack vectors.\nExperience deploying applications in cloud environments (AWS, Azure, or GCP).\nFamiliarity with containerization and orchestration tools (Docker, Kubernetes).\nExperience building RESTful APIs and microservices architectures.\n\nPreferred QualificationsMaster’s degree in Computer Science, Artificial Intelligence, or Cybersecurity.\nExperience designing AI systems for automated threat detection or exploit analysis.\nExperience with reinforcement learning, fine-tuning, or model evaluation frameworks.\nExperience integrating AI systems with cybersecurity tooling ecosystems.\nFamiliarity with NIST, ISO 27001, or similar security standards. \n\nOur Values \nWe 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. \nBe Excellent to Each Other\nDo the Right Thing \nDo What You’ll Say You’ll Do \nGet Better Together \nGive a Sh*t \nWe offer a variety of benefits and perks, such as: \nGenerous Time Off and Company-Wide Holidays \nHealth Insurance options including Medical, Dental, Vision \nRetirement; 401k matching for Traditional and Roth accounts in the US \nWork From Home Support \nMonthly allowance for cell phone and internet \nTraining Budget \nPaid Parental Leave \nSpecialty Occupation Justification \nThe 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. \nThe 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. \nBishop 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. 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