Lead Software Engineer- AI Red Team
Lead Software Engineer - GenAI for Cybersecurity Red Team.
Focused AI engineering role to build production-grade GenAI capabilities for cybersecurity use cases, with applied exposure to AI security and Red Team workflows.
Employment Type: - Full-Time.
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.
Required Skills & Experience
Area |
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.
