menlosecurity - Senior AI Security Engineer
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Requirements
• BSc in Computer Science or significant experience in high-scale cloud engineering; a relevant MSc or PhD is a strong advantage. • 3+ years of experience in applied AI, with a proven track record of deploying high scale AI systems in production environments. Agentic experience in production environments is an important advantage. • Expert-level Python; deep experience with k8s and cloud-native orchestration; proficiency with advanced data modeling and version control. • Significant experience in cybersecurity or browser-related technologies is highly preferred. • Deep understanding of prompt engineering techniques and how they can be exploited in agentic systems. • Ability to explore ambiguous problem spaces, experiment with new ideas, and iterate toward effective security solutions. • Hands-on experience with orchestration frameworks (e.g., LangChain, AutoGen) and / or standardized communication protocols like MCP. • Experience building immutable event streams and high-speed data pipelines for real-time traffic analysis. • Understanding of how web pages are rendered and how to programmatically manipulate the DOM or Accessibility Tree to enhance security. • A "security-first" mindset with a bias toward building auditable, traceable, and fault-tolerant systems.
Responsibilities
• Research Emerging Agentic Threats: Investigate new attack vectors against AI agents, including prompt injection, context poisoning, adversarial content embedding, and misuse of agent planning and reasoning mechanisms. • Architect Scalable Agentic Workflows: Design and implement robust, high-performance pipelines that secure agent-to-web interactions. • Develop Novel Detection & Mitigation Techniques: Design and prototype new approaches for identifying malicious prompts, unsafe contextual signals, and adversarial behaviors in LLM-powered agents. • Agent Security Controls: Implement these techniques as security controls within agentic runtimes, ensuring agents can safely reason over and act on external data sources. • Collaborative Engineering: Partner closely with applied engineers to integrate research-driven security mechanisms into production systems, balancing security effectiveness with agent performance. • Proactive Threat Modeling: Continuously evaluate the evolving AI threat landscape and anticipate future risks as agent capabilities and autonomy increase. • Adversarial Resilience: Build defensive mechanisms within the browser surrogate to detect and neutralize complex context poisoning and injection attempts embedded in web content.
Benefits
• Our culture is collaborative, inclusive, and fun! We have five core values: Stay Aligned, Get It Done, Customer Empathy, Think Creatively and Help Each Other Out. We believe in open communication, supporting new ideas, and sharing a mutual mindset of what we’re aiming to achieve together. There are tremendous opportunities to take initiative, implement new ideas, and have a hand in building a legacy.
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