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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Infrastructure Architect (2026 Vision)

Apex Horizon Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

We are pioneering the next generation of Autonomous Agentic AI infrastructure. As we look toward the technological landscape of 2026, we are seeking a visionary Senior AI Infrastructure Architect to design the backbone of our next-generation neural networks.

In this role, you won't just manage servers; you will architect the future of machine learning operations. You will be responsible for deploying scalable, low-latency inference engines that power autonomous decision-making systems. Join a elite team of engineers and researchers building the foundation for the next industrial revolution.

Why join us?

  • Work on cutting-edge AI models before they hit the mainstream.
  • Competitive compensation and equity package.
  • Remote-first culture with access to top-tier hardware.

Responsibilities

  • Architect and maintain high-performance GPU clusters optimized for 2026 inference workloads.
  • Design resilient Kubernetes-based pipelines for model deployment and scaling.
  • Collaborate with Research Scientists to optimize model quantization and latency.
  • Implement advanced security protocols for proprietary AI models.
  • Drive the migration of legacy infrastructure to cloud-native solutions.
  • Monitor system health and performance, implementing auto-scaling strategies to handle millions of requests.
  • Stay ahead of emerging trends in Quantum Computing and Edge AI integration.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • 7+ years of experience in Systems Engineering or DevOps with a focus on AI/ML.
  • Deep expertise in Python, PyTorch, TensorFlow, and CUDA programming.
  • Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Experience with MLOps tools (MLflow, Kubeflow, Airflow).
  • Proven track record of designing fault-tolerant distributed systems.
  • Familiarity with GenAI, LLM fine-tuning, and RAG architectures.

Required Skills

AI Machine Learning Python Kubernetes Cloud Computing DevOps PyTorch MLOps GPU Clustering System Architecture

Ready to Take This Challenge?

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