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Information Technology 🏒 Full Time ⭐️ Verified

Lead AI Architect: 2026 Ready Initiative

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

About Nexus Future Labs

We are the architects of tomorrow, building the foundational technologies that will define the year 2026 and beyond. We specialize in Agentic AI, autonomous systems, and quantum-inspired computing. We are looking for a visionary Lead AI Architect to lead our core research division.

The Role

You will be responsible for designing the next generation of autonomous AI agents that can reason, plan, and execute complex tasks in dynamic environments. This is not just about writing code; it is about defining the paradigm of artificial intelligence for the next decade. You will work directly with our CTO and a team of elite researchers to bridge the gap between theoretical AI and scalable production systems.

Why Join Us?

  • Work on 2026-ready technology stacks that are currently in the experimental phase elsewhere.
  • Competitive compensation and equity packages.
  • Unlimited PTO and a remote-first culture with a premium office in SF.
  • Access to cutting-edge hardware and cloud resources.

Responsibilities

  • Architect and deploy Autonomous AI Agents capable of multi-step reasoning and complex decision-making.
  • Lead the research and implementation of Agentic Workflows designed for the 2026 enterprise landscape.
  • Optimize large-scale model inference for Edge Computing environments.
  • Establish rigorous data pipelines and model governance frameworks.
  • Mentor a team of senior engineers and researchers, fostering a culture of innovation.
  • Collaborate with product teams to translate 2026 vision into technical roadmaps.

Qualifications

  • PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 10+ years of experience in Machine Learning, Deep Learning, or Distributed Systems.
  • Deep expertise in Python, PyTorch, and modern LLM frameworks.
  • Proven track record of shipping production-grade AI systems at scale.
  • Experience with Reinforcement Learning and Multi-Agent Systems.
  • Strong understanding of Quantum Algorithms or integration with classical systems.

Required Skills

Python PyTorch TensorFlow LLMs Machine Learning Reinforcement Learning Quantum Computing Distributed Systems Kubernetes AWS Agile

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