At Cerby we believe security is everyone’s business.  Collaborating across your apps doesn’t need to be chaos.  We are a mission-critical cybersecurity company that empowers your teams to operate securely and control their apps completely.  We’ve built our product on the idea that teams deserve autonomy over their work apps.  It turns out that why they are guaranteed a choice, security comes naturally.

More than 50% of all technology is spent outside of centralized IT organizations.  Individual business units are taking their technology destiny into their own hands, and we enable that.  End user onboarded applications are behind more than one third of all cybersecurity hacks.  We provide the solution to manage that through enabling users to select their own technology and we automatically protect those applications.

About the role

We are seeking a highly innovative AI/ML Engineer to lead the development of our next-generation agentic AI and traditional ML platform for cybersecurity applications. You will develop cutting-edge autonomous agents leveraging AI models from providers such as Anthropic, Google, Microsoft, OpenAI, and xAI, combined with the latest academic and industry research. Your focus will be on integrating, evaluating, and customizing these powerful models, enhancing their performance for specific security tasks, implementing guardrails, and ensuring robust security and privacy practices. This role requires deep AI/ML knowledge, and a passion for building intelligent systems that combine AI agents with ML and other techniques to drive deliver security solutions for our customers. A strong understanding of cybersecurity concepts is preferred, but not required.

What you'll do

System Architecture and Implementation

• Design the AI system, approach, and component architecture.
• Develop the foundations for the model and AI system development process.
• Integrate AI/ML models into our platforms.
• Collaborate with software development teams to embed AI functionalities into our SaaS products.

Evaluation

• Design a strategy and metrics for model performance evaluation.
• Develop automated systems and datasets for continuous model evaluation.
• Report on metrics and action plans to improve model performance.

Foundation Model Integration & Optimization

• Integrate state-of-the-art foundation models (LLMs, etc.) from various providers into our cybersecurity platform.
• Develop and implement strategies to maximize the performance of large language models (LLMs) for specific cybersecurity tasks, including techniques like prompt engineering, fine-tuning, Retrieval Augmented Generation (RAG), and other emerging methods.
• Develop solutions that utilize multiple modalities, including text and vision.

Agent Logic & Behavior Development

• Design and implement the core logic and decision-making processes for our autonomous agents.
• Develop intelligent agents capable of navigating complex environments including the public internet and private intranets, considering factors impacting performance.

Security & Privacy Integration

• Ensure security best practices and privacy considerations are integrated throughout the agent development process.
• Analyze attack vectors and privacy issues affecting AI agents and implement mitigation strategies.

AI Research & Strategy

• Stay current on AI and AI-related privacy concerns, especially in foundation models.
• Inform the company’s AI strategy by evaluating new models and relevant research.
• Contribute to technical documentation and share insights with the team.

Collaboration

• Work closely with cross-functional teams, including backend developers and product managers.
• Participate in code reviews, technical discussions, and project planning.

Qualifications

Education

• Bachelor's degree in Computer Science, AI, ML, or a related field. Master's or Ph.D. preferred.

Experience

• 3+ years applying ML to real-world problems, preferably in a cloud-based SaaS environment.
• 5+ years of experience building applications as a software engineer.

Technical Skills

• Deep understanding of AI/ML principles (evaluation, LLMs, prompt engineering, fine-tuning, transfer learning).
• Strong foundation in statistics and experimentation for AI/ML.
• Proficiency in Python and relevant AI/ML libraries.
• Familiarity with APIs for interacting with foundation models.
• Strong understanding of cybersecurity principles, attack vectors, and data privacy.
• Experience with LLM optimization techniques (fine-tuning, RAG, etc.).
• Strong research orientation and ability to adapt new techniques from research.

Desirable

• Experience with Node.js and TypeScript is highly desirable.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Proven experience integrating and customizing AI models from providers like OpenAI, Google, etc.
• Experience with reinforcement learning, variational auto-encoders, and representation learning.

Soft Skills

• Excellent problem-solving, analytical, and critical thinking skills.
• Strong collaboration and communication skills.
• Adaptability to the evolving AI landscape.
• Ability to learn new technologies and tools as needed.
• Attention to detail and commitment to high-quality work.