AI Engineering Team Lead - Applied AI Engineering Group

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:

It starts with you - an AI Engineering Team Lead responsible for leading a team building production-grade agentic systems. This role combines hands-on technical leadership with people management, ownership of architecture, delivery, and quality across agents, MCP tools, agentic workflows, RAG systems, and evaluation.

If you want to grow your skills building AI products for mission-critical AI, join Dream’s mission - this role is for you.

The Dream-Maker Responsibilities:

• Lead and mentor a team of AI Engineers building agentic systems and MCP tools.
• Own technical direction for agent architectures, workflows, and LLM evals.
• Review designs and code; ensure production readiness, reliability, and security.
• Drive adoption of frameworks such as LangChain, LangGraph, or equivalent.
• Set standards for RAG pipelines, vector databases, and retrieval quality.
• Partner with product and platform teams on roadmap, scope, and delivery.
• Balance hands-on contribution with people management and execution.
• Build a culture of strong engineering practices, measurement, and iteration.
  
  

• 6+ years software engineering experience; 4+ years building AI/ML systems.
• Prior experience as a technical lead or engineering manager.
• Deep understanding of agentic architectures and tool-based AI systems.
• Hands-on experience with MCP and agent tool integration.
• Experience with LangChain, LangGraph, or equivalent frameworks.
• Strong background in LLM evals, observability, and production AI quality.
• Solid experience with RAG pipelines, vector databases, and retrieval systems.
• Strong Python background and system design experience.