AI Architect

Role purpose

At Prevalent AI, we empower organizations to take control of every risk across every attack surface. Our clients rely on our cutting-edge Security Data Fabric as the foundation for comprehensive Exposure Management, enabling enhanced decision-making. By helping clients see everything, fix what matters, and stop attacks before they happen, we’re reshaping the future of security.

As an AI Architect, you'll lead strategic and technical AI initiatives, bridging business goals with scalable, sustainable solutions. You’ll design and implement AI-driven cybersecurity tools—built on knowledge graph foundations—to drive innovation in security intelligence.

Key accountabilities

• AI Strategy & Governance: Develops and maintains the overall AI strategy and technical roadmap, identifies new AI technologies, and establishes the governance frameworks, standards, and best practices for AI within the organization. This also includes leading the AI Center of Excellence and prioritizing AI initiatives based on strategic value.
• AI Consulting: Provides strategic consulting or the organisation in leveraging advanced AI, particularly knowledge graphs and LLMs, to build and deploy sophisticated, data-driven cybersecurity solutions for proactive threat identification and management
• Technical AI Architecture: Designs and implements enterprise-level AI/ML architectures, including cloud-native solutions and MLOps frameworks. This role ensures the scalability, security, and performance of AI systems and defines technical standards for model development, deployment, and monitoring, as well as data pipeline architectures.
• Team Leadership & Collaboration: Focuses on building and nurturing the AI team through mentorship and career development. This person also fosters innovation, facilitates knowledge sharing, and collaborates extensively with engineering, product, and business stakeholders.
• Innovation & Optimization: Drives continuous improvement by researching and prototyping emerging AI technologies, leading proofs-of-concept, and optimizing existing AI solutions. They also define performance metrics for AI systems and represent the organization in the broader AI community.

Skills and Experience

• Deep Technical Acumen: Possesses expert-level knowledge in AI/ML algorithms, system architecture, and cloud platforms, complemented by advanced skills in programming
  (Python/Scala), MLOps, and data engineering. This is further supported by proficiency in DevOps, software engineering best practices, and security.
• Strategic Technical Leadership: Demonstrates the ability to translate business needs into technical solutions, lead complex, multi-team technical initiatives, and make strategic long-term architectural decisions. This includes effective stakeholder management across both technical and business functions.
• Effective Communication & Influence excels at presenting complex technical concepts to diverse audiences, including executives. This individual can drive consensus on technical decisions across various teams and effectively document and communicate architectural choices, influencing outcomes even without direct authority.