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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Architect (2026 Roadmap)

Nexus Horizon Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

We are looking for a visionary Senior AI Architect to lead the development of our cutting-edge technology stack for the 2026 era. At Nexus Horizon Technologies, we are redefining the boundaries of Generative AI and Quantum Readiness. If you are passionate about building scalable, ethical, and futuristic systems that will define the next generation of human-machine interaction, we want to meet you.


In this role, you will not just build software; you will architect the future. You will collaborate with world-class researchers and engineers to design the neural infrastructure that powers our proprietary platforms. Join us in shaping the landscape of technology by 2026 and beyond.

Responsibilities

  • Architect and design scalable AI infrastructure and neural network architectures tailored for the 2026 technological landscape.
  • Lead the integration of Large Language Models (LLMs) and Generative AI into core product ecosystems.
  • Define the technical roadmap and best practices for MLOps, ensuring model deployment efficiency and reliability.
  • Collaborate with cross-functional teams (Data Science, Product, Engineering) to translate business goals into technical AI solutions.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
  • Ensure AI systems adhere to ethical guidelines, data privacy standards, and regulatory compliance.

Qualifications

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field (or equivalent practical experience).
  • 10+ years of experience in software engineering and at least 5 years in designing complex AI/ML systems.
  • Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks.
  • Proven track record of implementing LLMs and NLP solutions in production environments.
  • Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Experience with data engineering pipelines and big data technologies (Spark, Kafka).

Required Skills

Python TensorFlow PyTorch Machine Learning Deep Learning NLP MLOps AWS GCP Docker Kubernetes SQL Agile

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