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Senior AI Architect | 2026 Tech Visionary | Austin, TX

Quantum Horizon AI
Austin
Estimated Salary
USD 160.000 – USD 210.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

We are not just building software for today; we are architecting the technological landscape of 2026. Quantum Horizon AI is seeking a visionary Senior AI Architect to lead our R&D division. You will be at the forefront of Generative AI, Agentic workflows, and next-generation neural networks. If you are passionate about defining the future and solving complex scalability challenges, this is your opportunity to shape the industry.


Why Join Us?

  • Future-Ready Stack: Work with cutting-edge frameworks designed for the 2026 era.
  • Impact: Your code will power autonomous systems used by millions.
  • Culture: A diverse, high-performance environment that values innovation over hierarchy.

Key Responsibilities:

  • Design and deploy scalable machine learning infrastructure capable of handling petabyte-scale data streams.
  • Lead the technical strategy for 2026 AI capabilities, focusing on LLM optimization and multi-modal learning.
  • Collaborate with cross-functional teams to integrate AI models into real-world applications seamlessly.
  • Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
  • Conduct research on emerging AI paradigms to stay ahead of industry trends.
  • Ensure system security, reliability, and performance under high load.
  • Define and enforce best practices for model governance and ethical AI usage.

Qualifications:

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related field.
  • 5+ years of experience in designing large-scale machine learning systems.
  • Deep expertise in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
  • Proven track record of implementing Generative AI models in production environments.
  • Strong understanding of distributed systems, cloud architecture (AWS/GCP), and containerization (Docker/Kubernetes).
  • Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.
  • Experience with MLOps tools and CI/CD pipelines is highly desirable.

Responsibilities

  • Design and deploy scalable machine learning infrastructure capable of handling petabyte-scale data streams.
  • Lead the technical strategy for 2026 AI capabilities, focusing on LLM optimization and multi-modal learning.
  • Collaborate with cross-functional teams to integrate AI models into real-world applications seamlessly.
  • Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
  • Conduct research on emerging AI paradigms to stay ahead of industry trends.
  • Ensure system security, reliability, and performance under high load.
  • Define and enforce best practices for model governance and ethical AI usage.

Qualifications

  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related field.
  • 5+ years of experience in designing large-scale machine learning systems.
  • Deep expertise in Python, PyTorch, TensorFlow, or similar deep learning frameworks.
  • Proven track record of implementing Generative AI models in production environments.
  • Strong understanding of distributed systems, cloud architecture (AWS/GCP), and containerization (Docker/Kubernetes).
  • Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.
  • Experience with MLOps tools and CI/CD pipelines is highly desirable.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning Generative AI LLM AWS Kubernetes Docker MLOps System Design Data Science

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