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Information Technology 🏒 Full Time ⭐️ Verified

Principal AI Architect - Future Tech

Nexus 2026
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Welcome to the future. Nexus 2026 is at the forefront of the next technological revolution, bridging the gap between Generative AI and Quantum Computing infrastructure. We are not just predicting the future; we are building it.

We are seeking a visionary Principal AI Architect to lead our advanced engineering division. In this role, you will define the architectural blueprints for our next-generation systems, ensuring scalability, security, and innovation for the year 2026 and beyond.

If you are a technical leader who thrives in ambiguity and wants to shape the landscape of AI, we want to hear from you.

Responsibilities

  • Design and implement scalable, high-performance AI architectures for large-scale distributed systems.
  • Lead the integration of Quantum algorithms with classical machine learning models.
  • Define technical standards and best practices for AI model deployment and MLOps.
  • Mentor senior engineers and conduct architecture reviews to ensure code quality and system integrity.
  • Collaborate with product and research teams to translate business requirements into technical solutions.
  • Drive innovation in Generative AI, specifically focusing on Large Language Models (LLMs) and multimodal systems.
  • Ensure robust security protocols and data privacy compliance across all AI infrastructure.

Qualifications

  • Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
  • 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
  • Deep expertise in Python, PyTorch, TensorFlow, or JAX.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
  • Strong understanding of distributed systems, microservices, and system design patterns.
  • Proven track record of leading technical teams through complex product lifecycles.
  • Familiarity with ethical AI practices and bias mitigation in machine learning models.

Required Skills

Python Machine Learning Deep Learning Cloud Architecture MLOps Kubernetes AWS PyTorch System Design

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