Research Engineer; Physical AI

Position: Research Engineer (Physical AI)
Within the Agorai Innovation Hub we are looking for a talented and proactive resource, who will work directly with the AI Architect and Head of Technology, and in close collaboration with external engineering partners.

We are building the intelligence layer for autonomous and semi-autonomous systems operating in complex industrial environments. Robotics execution is handled by a partner — the researcher’s job is to make those systems smarter: multi-agent coordination, adaptive decision-making, collective behavior that emerges from local rules. The research direction includes swarm intelligence applied to real industrial problems, not simulations.

This role is fundamentally about integration — between research and reality, between AI systems and physical infrastructure, between your work and the engineering teams who own the hardware. You will need to earn technical credibility through the quality of your ideas and the reliability of your implementations.

Key responsibilities of the role will include:

Research and prototype multi-agent and collective intelligence approaches applicable to industrial automation — from simulation to integration with real systems

Build the intelligence and coordination layer that interfaces with physical systems and robotic infrastructure — you do not own the hardware, but you need to understand how to talk to it reliably

Design rigorous experiments that validate behavior at the system level, not just the component level — emergent properties require emergent evaluation

Integrate your AI systems with external engineering teams' stacks — this means clean interfaces, honest contracts, and the ability to debug across boundaries you do not fully control

Define evaluation frameworks for collective and adaptive behavior: what does it mean for the system to be working, and how do you know when it is degrading

Stay current with the research frontier in multi-agent systems, swarm intelligence, and autonomous systems — and bring back what is applicable

The role is based in Trieste and includes a hybrid work model, offering flexibility through remote working days.

Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, Engineering or a related STEM field

At least 3-5 years of previous experience in multi-agent systems, autonomous systems, or collective intelligence — academic or industry, but with real implementation behind it, not just theory

At least 3–5 years of experience in simulation tools and methodologies to develop and validate approaches before hardware integration

Experience in integrating AI systems with physical infrastructure or robotic platforms. Comfortable working with robotic middleware at an operational level

Technical Skills Fluent across the stack: LLM-based systems, classical ML, APIs, microservices, inference optimization

Strong software engineering fundamentals — your experimental code does not stay experimental forever, and you know when and how to make the transition

Comfort working at the boundary of research and engineering: you can run a controlled experiment, and you can write a production service, and you know when each is appropriate

Writing production-quality code and hold others to the same standard

Soft Skills & Personal Attributes Entrepreneurial mindset: takes ownership, operates with autonomy and drives things forward without waiting for direction

Ability to collaborate with external technical engineering teams

Excellent communication and stakeholder management skills; able to interact effectively with both technical teams and C-suite executives or institutional clients

Languages

English:
Full professional proficiency required (primary working language for international projects and publications)
Italian:
Knowledge of…