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Senior AI Security Engineer
Исключительная возможность работать в топовой компании в сфере кибербезопасности над передовыми технологиями защиты ИИ. Сильный состав инвесторов и работа с крупнейшими мировыми банками гарантируют стабильность и масштаб задач.
Сложность вакансии
Роль требует редкого сочетания глубоких знаний в области кибербезопасности (LLM vulnerabilities) и опыта разработки высоконагруженных облачных систем на Python и Kubernetes. Высокая сложность обусловлена необходимостью проводить исследования в новой, быстро меняющейся области безопасности ИИ-агентов.
Анализ зарплаты
Предлагаемая позиция Senior уровня в сфере AI Security в Великобритании обычно оплачивается выше среднего по рынку из-за дефицита специалистов на стыке ИИ и кибербезопасности. Ожидаемый диапазон составляет £90,000 - £130,000 в год плюс опционы.
Сопроводительное письмо
I am writing to express my strong interest in the Senior AI Security Engineer position at Menlo Security. With a robust background in high-scale cloud engineering and applied AI, I have closely followed Menlo's innovative approach to browser isolation and web security. The challenge of securing autonomous AI agents against prompt poisoning and context manipulation is one of the most critical frontiers in cybersecurity today, and I am eager to bring my expertise to your R&D team.
In my previous experience deploying production-grade AI systems, I have developed a deep understanding of LLM vulnerabilities and the complexities of agentic workflows. I am particularly drawn to Menlo's mission of enabling secure collaboration without compromise, especially given your impressive client base of Fortune 500 companies and global banks. My proficiency in Python, Kubernetes, and adversarial threat modeling aligns perfectly with your requirements for building resilient defensive mechanisms within the browser surrogate.
I am excited about the opportunity to contribute to a company that values creative thinking and customer empathy. I look forward to the possibility of discussing how my technical skills and security-first mindset can help Menlo Security stay ahead of emerging agentic threats.
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Описание вакансии
Menlo Security's mission is enabling the world to connect, communicate and collaborate securely without compromise. COVID-19 has made our mission all the more real. We support customers across various enterprises including Fortune 500 companies, 9/10 of the largest global banks and the Department of Defense.
The world has fundamentally changed. We are growing from 400 employees into the next phase of our journey, and we need passionate talent filled with empathy and agility. The right candidate for the job is ethical, hyper-organized, fanatical about seeing things through to completion, service-oriented, and humble enough to take feedback and coaching yet confident enough to provide feedback and coaching.
Menlo is well-funded for growth and our investors are second to none. They include Vista Equity Partners (“Vista”), General Catalyst, JPMC, American Express, HSBC, and Ericsson Ventures.
We are seeking a Senior AI Security Engineer to focus on the emerging security challenges of autonomous AI agents. In this role, you will research, design, and implement novel techniques to detect and mitigate prompt poisoning, context manipulation, malicious agent behaviors, and other adversarial threats targeting agentic AI systems.
You will work closely with engineering teams to translate cutting-edge security research into practical, deployable security controls that protect agents operating in real-world environments, particularly when interacting with untrusted web content.
Core 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.
Qualifications
- 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.
Nice to Have
- 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.
MSGL-I4
Why Menlo?
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.
All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.
*TO ALL AGENCIES: Please, no phone calls or emails to any employee of Menlo Security outside of the Talent organization. Menlo Security’s policy is to only accept resumes from agencies via Ashby (ATS). Agencies must have a valid services agreement executed and must have been assigned by the Talent team to a specific requisition. Any resume submitted outside of this process will be deemed the sole property of Menlo Security. In the event a candidate submitted outside of this policy is hired, no fee or payment will be paid.*
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Навыки
- Cybersecurity
- Python
- Threat Modeling
- LLM
- Kubernetes
- Prompt Engineering
- Data Modeling
- LangChain
- Cloud Native
- Autogen
Возможные вопросы на собеседовании
Проверка понимания специфических угроз для ИИ-агентов, упомянутых в описании.
Можете ли вы описать разницу между классической prompt-инъекцией и context poisoning в контексте автономных агентов?
Оценка практического опыта работы с инструментами оркестрации, указанными в вакансии.
Какие основные риски безопасности вы видите при использовании фреймворков типа LangChain или AutoGen в продакшене?
Проверка навыков проектирования защитных механизмов.
Как бы вы спроектировали систему мониторинга в реальном времени для обнаружения аномального поведения агента, взаимодействующего с внешним веб-контентом?
Оценка опыта работы с облачной инфраструктурой.
Опишите ваш опыт обеспечения безопасности контейнеризированных ИИ-приложений в среде Kubernetes.
Проверка навыков анализа веб-технологий для защиты браузера.
Как манипуляции с DOM или Accessibility Tree могут помочь в предотвращении атак на ИИ-агентов, работающих через браузер?
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