Senior AI Engineer

Posted 3 Days Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Artificial Intelligence • Machine Learning • Software • Quantum Computing
The Role
Design, deploy, and maintain production-grade LLM architectures and autonomous agentic AI systems. Collaborate with scientists, engineers, and customers to solve complex problems, lead cross-functional technical initiatives, translate business goals into roadmaps, and promote reliable, observable, safe, high-quality engineering. Mentor teams, conduct architecture and code reviews, and advance systems involving RAG, fine-tuning, agent memory, evaluation, vector databases, distributed computing, GPU optimization, and quantum computing.
Summary Generated by Built In

Join Qutwo - Europe's private Quantum AI Lab, on our quest to bridge the gap between the classical and the quantum world. We partner with the most advanced and forward-thinking customers, solving fundamental real-world problems, side by side.

The best scientists and engineers in the world are drawn to one thing: a problem worthy of their ability. At Qutwo, we have one. We are a European AI lab for the quantum era, co-founded by pioneers behind IQM and Silo AI, with a team spanning MIT, UC Berkeley, Cambridge, and Carnegie Mellon, and backed by the founders of Skype, Hugging Face, Quantinuum, Supercell and many more. We work at the intersection of quantum computing, AI, optimization, and simulation — where the answers do not yet exist and the work genuinely matters.

We are seeking exceptional AI/ML Engineers. If you are a humble learner, not afraid of the unknown, we encourage you to apply.

Role Description

As a Senior AI/ML Engineer, you will join our team in a full-time capacity, collaborating closely with our scientists, engineers, and customers. In this role, you will apply a blend of exploratory research and practical implementation to design production-grade LLM architectures and autonomous Agentic AI systems that solve complex, real-world problems and drive customer value.

Qualifications
  • Proven track record of designing, deploying, and maintaining end-to-end ML systems and production-grade LLM applications at scale. You have owned the transition from prototype to production-hardened service.

  • 5+ years of professional experience in ML/AI Engineering. You prioritize robust system design, observability, safety/guardrails, and "infrastructure as code" over one-off experiments.

  • Hands-on experience architecting Agentic AI systems, including multi-agent coordination, stateful workflow orchestration, autonomous decision loops, and complex action execution.

  • Strong background in LLM integration, including function calling/tool-use, structured output parsing, and advanced reasoning strategies.

  • Exceptional ability to lead cross-functional initiatives, translate business objectives into technical roadmaps, and uphold high standards for code quality and system reliability.

  • Experience leveling up high-performing engineering teams, conducting deep-dive code/architecture reviews, and fostering a culture of technical excellence.

Experience in one or more of the following areas is a plus:

  • Deep experience in LLM infrastructure, including advanced RAG systems, model fine-tuning, agent memory architectures, and automated evaluation frameworks.

  • Proficiency with vector databases, distributed computing, and GPU optimization.

  • Familiarity with combinatorial optimization algorithms or the intersection of ML and Quantum Computing.

Skills Required

  • Proven experience designing, deploying, and maintaining end-to-end machine learning systems and production-grade LLM applications at scale.
  • 5+ years of professional experience in ML/AI engineering.
  • Experience taking ML and LLM prototypes into production-hardened services.
  • Experience architecting agentic AI systems, including multi-agent coordination, stateful workflow orchestration, autonomous decision loops, and complex action execution.
  • Strong experience integrating LLMs, including function calling, tool use, structured output parsing, and advanced reasoning strategies.
  • Ability to lead cross-functional initiatives and translate business objectives into technical roadmaps.
  • Experience maintaining high standards for code quality and system reliability.
  • Experience mentoring or leveling up high-performing engineering teams.
  • Experience conducting detailed code and architecture reviews.
  • Deep experience with LLM infrastructure, including advanced RAG, model fine-tuning, agent memory architectures, and automated evaluation frameworks.
  • Proficiency with vector databases, distributed computing, and GPU optimization.
  • Familiarity with combinatorial optimization algorithms or the intersection of machine learning and quantum computing.
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The Company
Year Founded: 2026

What We Do

Qutwo is a European AI lab focused on creating next-generation AI for a quantum world. The company develops enterprise software and the Qutwo OS, an orchestration layer that bridges classical and quantum computing. By simulating quantum workloads and offering hybrid solutions, Qutwo helps enterprises solve complex optimization and simulation problems and prepare for the transition to full quantum advantage.

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