About MCIM

MCIM – The Data Center Operating System (DCOS) is a platform that simplifies the complexities of managing a data center by bringing all functions and locations under one intuitive dashboard. 

MCIM started with a commission from a Fortune 100 financial institution to create a cloud computing solution for managing their global critical facilities. The team developed the MCIM platform based on the lessons learned from that project.

Today, MCIM is utilized by Fortune 100 and 500 companies in over 94 countries worldwide. This world-class solution is continuously improved through collaboration with users and industry organizations like The Uptime Institute.

We are seeking a hands-on and inventive AI Engineer to join MCIM Labs—a fast-moving innovation team reporting directly to the founder. In this role, you won’t be researching models in theory—you’ll be building and shipping functional AI prototypes that demonstrate real business value. You will leverage agentic frameworks like LangChain, CrewAI, and Autogen to rapidly design and deploy multi-agent systems and LLM-based tools. This role is full-stack in nature, blending AI engineering, application logic, and lightweight UI development to move fast from concept to demo. You will collaborate closely with data engineers, product visionaries, and technical stakeholders to push the boundaries of what’s possible with enterprise AI. Your work will directly influence the development of new data-driven products and revenue-generating capabilities within MCIM.

What You’ll Do:

• Rapid AI Prototyping
  Use generative and agent-based tools (LLMs, Replit Agent, etc.) to build functional proof-of-concepts using real MCIM data.
• Multi-Agent Orchestration
  Build and manage autonomous agents capable of coordinating within MCIM’s enterprise SaaS workflows.
• Performance & Integration Tuning
  Partner with Data Engineering to align models with MCIM’s ontology and ensure system performance, scalability, and reliability.
• Full-Stack System Design
  Connect front-end interfaces with back-end AI logic to create end-to-end MVPs with real user value.

Who You Are:

• A scrappy builder with a track record of hands-on experimentation using tools like LangChain, Hugging Face, PyTorch, TensorFlow, etc.
• Comfortable working solo or in small teams to move from idea → demo quickly.
• Understand how to implement LLMs and agents to solve real problems—not just theorize about them.
• Familiar with modern data architectures, prompting strategies, and end-to-end software delivery.

What You Bring:

• Proven experience delivering AI/ML solutions (LLM integrations, agentic workflows, full-stack prototypes)
• Comfort with tools like LangChain, Autogen, CrewAI, Replit, and Hugging Face
• Programming comfort (Python preferred) and ability to connect AI logic to live data backends
• Experience working with structured and unstructured data; SQL knowledge a plus
• Self-starter mindset with strong curiosity, communication, and collaboration instincts

Preferred Qualifications:

• 5+ years in software engineering, AI product development, or full-stack roles
• Experience with prompt engineering and LLM APIs
• Prior work inside a fast-paced innovation or R&D group preferred
• Bachelor’s degree in a technical field is a plus—but hands-on proof of ability matters most