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Lead AI Architect: 2026 Readiness Initiative

Nexus Horizon Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

We are seeking a visionary Lead AI Architect to spearhead our 2026 Readiness Initiative. As the landscape of artificial intelligence accelerates, Nexus Horizon Systems is building the next generation of sentient, self-correcting machine learning models. In this role, you will define the technical roadmap for our flagship product, ensuring our infrastructure is future-proofed for the 2026 era of generative autonomy.

You will collaborate with world-class engineers and data scientists to deploy scalable, secure, and ethical AI systems. If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.

Responsibilities

  • Architect and implement next-generation neural networks designed for the 2026 computing paradigm, including quantum-ready algorithms.
  • Lead a team of 10+ ML engineers to build and deploy high-throughput inference engines for autonomous agents.
  • Define the technical vision for our transition to edge-computing AI, ensuring low-latency responsiveness in real-time environments.
  • Establish best practices for AI ethics, safety, and governance to ensure compliance with evolving 2026 regulatory standards.
  • Mentor junior engineers and foster a culture of continuous innovation and technical excellence.
  • Conduct proof-of-concept research on emerging technologies, such as Neuromorphic Computing and Synthetic Data Generation.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related field with a focus on Deep Learning.
  • 10+ years of experience in software engineering and machine learning, with at least 5 years in a leadership capacity.
  • Expert knowledge of Python, PyTorch, TensorFlow, and distributed systems.
  • Proven track record of deploying large-scale LLMs (Large Language Models) and multi-modal AI systems.
  • Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker).
  • Strong understanding of optimization techniques for future hardware architectures (TPU, GPU, Quantum processors).

Required Skills

Artificial Intelligence Machine Learning Neural Networks Python Deep Learning Cloud Architecture Distributed Systems Leadership Quantum Computing

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