Director of AI Agents Research

At Dream, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; It’s a Dream job. Dream is where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Let’s build something extraordinary together.

Dream's AI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our Dream's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.

At Dream, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.

The Dream Job:

We’re on an expedition to find someone who’s passionate about creating intuitive, out-of-this-world scalable, high-performance systems that power the future of AI. You'll lead an organization of engineers , MLOps teams, and more to redefine the next AI agentic infrastructure for multiple use cases across the product and organizations.

The Dream-Maker Responsibilities:

• Suggests AI strategy aligned with company goals (e.g., automation, personalization, product innovation).
• Oversees AI research and development Mannaging Engineers , AI engineering, and MLOps teams.
• Evaluates AI opportunities — identifies where AI can deliver value and ensures ethical, scalable implementation.
• Collaborates with executives to translate business needs into technical roadmaps.
• Builds AI governance: compliance, ethics, and model accountability frameworks.
• Collaborate with Engineering, Product, Security
  
  

• 8+ years in AI/ML, with at least 3–5 years in a leadership role.
• Knowledge in AI agents and orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph).
• Understanding of machine learning algorithms, LLMs, and generative AI.
• Understanding in Edge AI and multimodal systems (text, vision, voice).
• Executive communication — translating complex AI concepts into ROI-focused narratives.
• Expertise in data architecture, ETL pipelines, and data governance.
• Familiarity with cloud AI platforms (AWS Sagemaker, Google Vertex AI, Azure AI Studio).
• Understanding of MLOps, CI/CD for models and AI agents, monitoring.