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Information Technology 🏢 Full Time ⭐️ Verified

Principal AI Architect (2026 Vision)

Apex Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are standing on the edge of a new era of intelligence. As we look toward the horizon of 2026, the integration of Artificial Intelligence into every layer of the digital ecosystem is no longer a possibility—it is an inevitability. Apex Horizon Labs is seeking a visionary Principal AI Architect to lead our research and development division in defining the technological landscape of the future.

In this role, you will not simply maintain current systems; you will architect the neural frameworks and autonomous decision-making engines that will power the next generation of global infrastructure. We are looking for a technical leader who thrives in ambiguity and is obsessed with pushing the boundaries of what is computationally possible.

Join us in building the intelligent backbone of tomorrow, today.

Responsibilities

  • Architect and lead the design of scalable, high-performance AI systems for the 2026 strategic roadmap.
  • Oversee the research, development, and deployment of next-generation Deep Learning models and neural networks.
  • Collaborate with product and engineering teams to integrate cutting-edge AI capabilities into core business solutions.
  • Establish architectural standards for data governance, model training, and edge computing deployment.
  • Drive innovation in AI hardware acceleration and quantum-ready software interfaces.
  • Mentor senior engineering teams and foster a culture of technical excellence and forward-thinking.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
  • 10+ years of experience in AI/ML engineering, with at least 5 years in a senior architectural leadership role.
  • Deep proficiency in Python, C++, and major ML frameworks (PyTorch, TensorFlow, JAX).
  • Proven track record of deploying large-scale machine learning models in high-traffic production environments.
  • Strong understanding of distributed systems, cloud infrastructure (AWS, GCP, Azure), and containerization (Docker, Kubernetes).
  • Experience with neuro-symbolic AI or quantum computing interfaces is highly desirable.

Required Skills

Artificial Intelligence Machine Learning Deep Learning Python C++ System Architecture Cloud Computing Neural Networks Distributed Systems TensorFlow PyTorch

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