AI Application Engineer

Univers provides the world's most comprehensive decarbonization system.

We help companies and countries optimize energy systems and reduce carbon emissions with accurate, reliable, and actionable decarbonization data. Our EnOS (Energy and Environment Operating System) platform connects on-the-ground operational technology and in-the-cloud intelligence to deliver real-time energy data and data-driven carbon monitoring, reporting, and abatement.

With 220 million sensors and smart devices connected, 550GW of renewable energy under management, and a community of over 500 customers, we're helping the world's leading businesses get the world to net zeroand what comes after it.

For more information, please visit https://univers.com/

The Role:

We're looking for a proactive and creative AI Innovation Engineer to join our mission. You will be key in identifying opportunities within the Smart Building domain and leveraging Large Language Models (LLMs), potentially Reinforcement Learning (RL), and software engineering skills to design and build groundbreaking AI Workbench. If you're passionate about shaping the future of buildings with AI, this role is for you.

Key Responsibilities:

• Translate Needs: Understand unique challenges and opportunities in the Smart Building sector and translate them into viable AI Workbench concepts.
• Develop & Deploy: Build, test, and deploy robust AI-driven applications (utilizing LLMs, exploring RL) specifically tailored for building operations, energy management, user experience, or related areas.
• Abstraction and Governance: Addressing various application scenarios in the Building domain, participate in the symbolic governance work within Workbench.
• Skill Building: Provide standardized skill and plugin building for different capabilities in Workbench.
• Innovate & Collaborate: Stay current with AI advancements, experiment with new approaches, and work closely with building experts.

Qualifications:

• Proven experience in software development (Python strongly preferred).
• Hands-on experience applying Large Language Models (LLMs) via APIs, Prompt Engineering, RAG, etc. Basic understanding of Reinforcement Learning (RL) is a plus.
• Strong problem-solving skills and the ability to connect business needs (ideally within the building, IoT, or energy sectors) to technical AI solutions.
• Excellent communication and teamwork abilities.
• Self-driven with a passion for AI and innovation in the Smart Building space.