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Lead AI Architect (2026 Vision)

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

Job Description

Are you ready to define the technological landscape of 2026 and beyond? Nexus Horizon Technologies is seeking a visionary Lead AI Architect to spearhead our research and engineering initiatives. We are not just building software; we are architecting the future of generative intelligence.

In this pivotal role, you will move beyond standard implementation to design the foundational models and infrastructures that will power the next era of human-computer interaction. You will work at the intersection of theoretical research and scalable production systems, ensuring our solutions remain ahead of the curve in a rapidly evolving market.

Join a world-class team where your work will have a direct impact on industries ranging from healthcare to autonomous logistics.

Why Join Nexus Horizon?

  • Work with state-of-the-art Generative AI and LLM technologies.
  • Competitive compensation and equity packages.
  • Flexible remote-first culture with access to premium tech infrastructure.
  • Opportunity to mentor the next generation of AI engineers.

Responsibilities

  • Design and deploy scalable architectures for Large Language Models (LLMs) and Agentic AI workflows.
  • Lead the research and implementation of novel neural architectures and optimization techniques.
  • Build robust Retrieval-Augmented Generation (RAG) pipelines to ensure data accuracy and relevance.
  • Collaborate with product and engineering teams to integrate AI capabilities into core product ecosystems.
  • Establish best practices for model monitoring, evaluation, and governance.

Qualifications

  • Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in machine learning engineering or data science.
  • Deep expertise in Python, PyTorch, TensorFlow, or JAX.
  • Proven track record of deploying production-grade ML models at scale.
  • Strong understanding of distributed systems, cloud infrastructure (AWS/GCP), and containerization (Docker/Kubernetes).

Required Skills

Python PyTorch TensorFlow Machine Learning LLM RAG Kubernetes AWS Deep Learning Distributed Systems

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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