Description

Join Cynomi as our first full-time AI engineer and help transform our platform with cutting-edge AI technologies. You’ll play a key role in developing and integrating innovative AI solutions to enhance our products and services. Collaborate with cross-functional teams to explore and implement the latest AI advancements, driving meaningful impact on the company’s growth and success.

About us

Cynomi is a fast-growing, Silicon Valley VC-backed cybersecurity startup. Experiencing massive growth over the past year, our SaaS product is used by hundreds of service providers worldwide.

Operating across three continents, Cynomi is leading the vCISO (virtual Chief Information Security Officer) market category with rapidly growing demand for its AI-powered vCISO platform, which empowers service providers (MSPs and MSSPs) to provide high quality cybersecurity services to their customers.

Key Responsibilities

• Design and implement AI solutions tailored to business needs, including Generative AI and Large Language Models (LLMs).
• Develop and optimise Retrieval-Augmented Generation (RAG) architectures and fine-tune model outputs.
• Build and deploy AI agents and infrastructure to support training and deployment of AI models.
• Optimise workflows for large datasets, distributed training, and model evaluations.
• Collaborate with teams to integrate AI-driven features into products.
• Stay current with AI trends, security best practices, and share knowledge with the team.
• Document architectures, processes, and lessons learned effectively.

Requirements

• Proven experience in AI development, including both Classical AI techniques (e.g., decision trees, regression, clustering) and Generative AI models (e.g., GANs, transformers).
• Proficiency in programming languages such as Python or Java
• Strong understanding of model evaluation techniques, including Confusion Matrices, and metrics like accuracy, precision, recall, and F1-score.
• Familiarity with data preprocessing, feature engineering, and model tuning.
• 2+ years experience applying AI to practical and comprehensive technology solutions. 
• 5+ years relevant experience such as software development.

Advantages

• Experience with sophisticated RAG and / or agent based systems.
• Experience with graph-based algorithms
• Familiarity with knowledge graphs and graph databases,
• University level qualification in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for AI/ML deployment.
• Knowledge of modern MLOps practices for managing the AI lifecycle.
• Background in developing explainable AI solutions and addressing ethical considerations.
• Understanding of domain-specific AI applications relevant to the industry.