Lead Cybersecurity Engineer- AI Red Team
Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Aug 4, 2026. Société Générale scores B on the Alion truth index.
Responsibilities
Focused AI engineering role to build production-grade GenAI capabilities for cybersecurity use cases, with applied exposure to AI security and Red Team workflows.
Experience: - 8+ years overall; strong hands-on AI/GenAI engineering and platform delivery experience.
Primary Depth: - GenAI engineering, LLM/RAG platforms, scalable AI solution delivery.
Secondary Exposure: - Cybersecurity domain understanding, AI security risks, Red Team use cases.
We are looking for a Lead Software Engineer with strong depth in GenAI engineering and platform delivery to build AI-enabled capabilities for cybersecurity teams.
The core expectation is not to find a single expert across GenAI, cybersecurity, AI security, and Red Teaming. The role should primarily focus on designing and delivering production-grade LLM/RAG solutions, while using cybersecurity and Red Team exposure to ensure the solutions are practical, secure, and relevant to real-world security operations.
Key Responsibilities· Design, build, and industrialize GenAI solutions using LLMs, RAG, embeddings, vector search, agents, APIs, and orchestration frameworks.
· Own platform engineering aspects including ingestion pipelines, observability, evaluation, CI/CD, monitoring, security controls, and operational readiness.
· Partner with cybersecurity stakeholders to translate threat analysis, investigation, and security automation needs into AI-enabled workflows.
· Apply working knowledge of AI security risks such as prompt injection, data leakage, hallucination, model misuse, and unsafe tool usage.
· Collaborate with Red Team or offensive security teams to support use-case design, validation, and practical adoption without making deep Red Team expertise mandatory.
Profile required
Required Skills & ExperienceArea
Expectation
Primary Depth
Strong hands-on GenAI engineering experience with LLMs, RAG, embeddings, vector databases, prompt engineering, evaluation, and production deployment.
Platform Engineering
Ability to design scalable AI systems covering APIs, orchestration, pipelines, monitoring, observability, CI/CD, and operational controls.
Engineering
Strong Python or backend engineering skills, secure software development, microservices, cloud-native design, and integration with enterprise systems.
Cybersecurity Exposure
Working understanding of cybersecurity concepts such as threat analysis, vulnerability management, identity, cloud security, security telemetry, and risk controls.
Preferred / Good-to-Have Exposure· Exposure to AI security topics such as prompt injection, jailbreaks, data leakage, model abuse, hallucination, and insecure agentic workflows.
· Familiarity with Red Team, penetration testing, adversary simulation, MITRE ATT&CK, or purple team practices.
· Experience integrating AI capabilities with SIEM, SOAR, EDR, threat intelligence, vulnerability management, or cloud security platforms.
· Experience working in regulated enterprise environments with governance, auditability, and responsible AI expectations.