Senior AI Engineer - 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 - a senior AI engineer focused on building production-grade agentic systems: autonomous agents, MCP tools, agentic workflows, and rigorous 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:

• Design and build single- and multi-agent systems with planning, memory, and tool use.
• Implement and operate MCP tools and servers with secure schemas and permissions.
• Build agentic workflows using LangChain, LangGraph, or equivalent frameworks.
• Integrate LLMs via SDKs; manage prompts, structured outputs, and tool calling.
• Define and run LLM evals (quality, correctness, latency, cost, regressions).
• Add observability and reliability (logging, tracing, retries, state management).
• Optimize performance and cost; take systems to production.
• Mentor engineers and establish agentic best practices.
  
  

• 4+ years software engineering; 2+ years production AI/ML systems.
• Hands-on experience with agentic architectures and tool calling.
• Practical experience with MCP.
• Experience with LangChain, LangGraph, or equivalent frameworks.
• Proven experience designing and operating LLM evals.
• Strong Python and API design skills.
• Familiarity with RAG pipelines, vector databases, and embedding-based retrieval systems (indexing, chunking, filtering, relevance tuning).