DevJobs

Senior Applied AI Engineer – Agentic Systems (PhD)

Overview
Skills
  • Python Python
  • agentic architectures
  • decision-making
  • LLM
  • planning
  • reinforcement learning
  • autonomous systems
  • robotics
  • simulation
  • world modeling

About the Role

We are building a new layer of intelligence that bridges models and real-world decisions — enabling agentic systems to reason, plan, and execute reliably over time. We are looking for a hands-on Senior Applied AI Engineer (PhD) to design and implement production-grade agentic systems. This role is focused on turning advanced AI concepts into real, scalable, and reliable systems.

What You’ll Do

• Design and implement agentic AI architectures (reasoning loops, planning, memory, tool use, multi-step execution).

• Build stateful systems that operate across time and evolving context.

• Integrate LLMs into robust production pipelines (orchestration, evaluation, guardrails).

• Develop decision-making systems under uncertainty and partial observability.

• Translate research ideas into working systems with strong engineering discipline.

• Improve reliability, monitoring, and system performance.

Requirements:

• PhD in Computer Science / AI / Machine Learning / Robotics or related field.

• Strong hands-on coding skills (Python required).

• Experience building real AI systems beyond research prototypes.

• Background in planning, reinforcement learning, decision-making, or agentic architectures.

• Experience working with LLM-based systems in production environments.

• Strong system-level thinking (state, latency, failure modes, scalability).

Nice to Have (Advantage)

• Experience with Physical AI / embodied systems.

• Background in simulation or world modeling.

• Experience in robotics, autonomous systems, or real-world execution environments.

Cortica