> Markdown version of [/jobs/ext/4627042-ai-security-engineer](https://www.wearedevelopers.com/jobs/ext/4627042-ai-security-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Security Engineer - **Company:** Insight Global - **Location:** San Jose, CA, United States - **Experience:** Expert - **Salary:** $180,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Code Optimization, Cyber Security, Databases, Intrusion Detection and Prevention, Python (Programming Language), Performance Tuning, OpenAI, Security Information and Event Management, Software Vulnerability Management, QLoRA, DeepSpeed, Large Language Models, Cyber Threat Analysis, Agentic-AI, Discretization, CrewAI, AutoGen, ChromaDB - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25303_688f06f137bc09372a46dd5d9b32a720 ## About the Role 8 years experience as a Cyber Security Engineer, with hands-on experience in security research, threat intelligence, vulnerability management, red teaming, or detection engineering -Experience working with LLMs, using them to solve cybersecurity challenges -Experience with retrieval tools such as LangChain, and ChromaDB -Experience using Fine-tuning techniques and tools including LoRA, QLoRA, DeepSpeed-Chat / TRL, OpenAI Fine-Tuning API, MosaicML Platform -Experience using LLM Agent frameworks such as LangChain Agents, AutoGPT, Microsoft AutoGen, HuggingGPT, CrewAI -Experience using optimization tools such as Quantization, FlashAttention, Distillation, DeepSpeed-Inference / FasterTransformer ## Description Insight Global is hiring a AI Cyber Security Engineer join the team, based out of San Jose, CA. This person will be focused on gathering research dependent on requirements from the customers and figuring out what is the most efficient way to automate their issues using LLMs. This person will spend about 75% of their time researching areas like vulnerability management, CVE databases, and SIEM logs, and 20-25% coding in Python to prototype and connect tools for the engineering team. They will work with existing LLMs and vector databases (e.g., LangChain, ChromaDB, MosaicML) to configure secure solutions. The ideal candidate will have experience in a security firm or on a security-focused team, are self-driven researchers, and can bridge AI with cybersecurity.