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In office (Madrid)
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Sponsors visas in United Kingdom; no register of this country names it
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 7, 2026. First seen by Alion on Sep 3, 2026. Univers scores B on the Alion truth index.

Overview
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Impact
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Univers provides an enterprise decarbonisation platform combining energy, emissions and asset data. Its EnOS operating system manages renewable and industrial assets at scale. The company is headquartered in Singapore.

The Company:

Univers is the global leader in AI for energy.

Univers operates one of the world’s largest real-time intelligence platforms for physical infrastructure, connecting over 400 million sensors and devices and managing more than 1,005 GW of energy assets.

Through its Platform for Physical AI, Univers helps organizations orchestrate complex energy, infrastructure and operational systems with intelligence that continuously learns and improves over time.

Our EnOS™ platform empowers enterprises across industries to solve complex energy challenges with intelligent, data-driven insights.

The challenge is immense, but so are the rewards. Join our team and help move the planet towards sustainability. For more information, please visit https://univers.com

Job Overview: Forward Deployed Engineer

Are you looking to use AI and modern technology to solve real-world problems and transform how organisations operate?

Univers is accelerating the next generation of AI and intelligent IoT innovation, helping businesses, industries, critical infrastructure operators, and other organisations transform operations, optimize resources, improve resilience, and make better decisions at scale.

Our mission is to translate advances in AI into real-world systems that improve operational performance, energy efficiency, sustainability, and productivity. We focus on applied intelligence, where AI models, agents, data, and operational systems come together in real workflows and continuously improve through feedback.

AI is moving from promise to accountability. Organizations increasingly expect AI to move beyond isolated demonstrations and deliver measurable outcomes in complex, real-world environments.

If you are motivated by solving difficult problems, working closely with customers and users, rapidly building working solutions, and learning across technology, product, business, and operations, this is an opportunity to turn AI innovation into real-world impact.

Job Role Overview:

As a Forward Deployed Engineer at Univers, you will work at the intersection of customers, technology, and product to help organizations adopt AI and the Univers platform successfully.

You will work closely with customers and cross-functional teams to understand business and operational workflows, create clarity from ambiguous problems, decompose complex challenges into actionable solutions, and rapidly develop demos, prototypes, pilots, and production solutions.

You will learn to effectively leverage Univers' platform, AI models, modern development tools, data, and system integrations to deliver value quickly. You will also help identify reusable solution patterns and platform improvements that can benefit future deployments.

This role is designed for recent graduates with a Bachelor's degree or above. Prior full-time work experience is not required. Relevant internships, university projects, research, hackathons, startup experience, or other hands-on technical experience are a plus.

Key Responsibilities:

  • Work with customers and teams to understand business problems, operational workflows, and desired outcomes
  • Clarify and decompose complex problems into practical, actionable solutions
  • Rapidly build and iterate demos, prototypes, pilots, and production solutions using Univers' platform, AI, and modern development tools
  • Integrate data, APIs, systems, and applications into end-to-end solutions
  • Learn and effectively leverage Univers' product and platform capabilities to maximize reuse and accelerate delivery
  • Collaborate across GTM, Product, AI teams, and customer teams to deliver solutions and iterate based on feedback
  • Identify reusable solution patterns and platform improvements that can scale across future deployments

Qualifications:

  • Bachelor's degree or above in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Physics, or a related technical discipline
  • Strong software engineering fundamentals and programming skills
  • Good understanding of AI and machine learning, including familiarity with technologies such as LLMs, multimodal models, and AI agents
  • Strong analytical and structured problem-solving skills, with the ability to break complex and ambiguous problems into manageable pieces
  • Ability to learn new technologies, platforms, industries, and operational domains quickly
  • Comfortable working across both technical and business topics
  • Strong communication and collaboration skills
  • Hands-on, curious, adaptable, and comfortable working in fast-moving environments
  • Strong ownership and interest in solving real customer and operational problems

Preferred Qualifications:

  • Relevant internship experience in software engineering, AI/ML, data science, solution engineering, product, consulting, or related areas
  • Experience building software applications, AI applications, agents, prototypes, or other end-to-end technical projects
  • Experience with databases, data integration, cloud platforms, or modern application development
  • Experience using AI-assisted development tools and coding assistants
  • Experience through research projects, hackathons, startups, student organizations, or other activities demonstrating initiative and end-to-end ownership
  • Experience working in multidisciplinary teams or communicating technical concepts to non-technical audiences

What Success Looks Like:

Success in this role will be defined by your ability to learn quickly, create clarity from ambiguity, connect real-world needs with technology and platform capabilities, rapidly build and iterate working solutions, and contribute to measurable outcomes while identifying reusable capabilities that can scale across future deployments.

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