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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Infrastructure Architect (2026 Roadmap)

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

Job Description

Shape the Future of Intelligent Systems

Nexus Horizon is pioneering the infrastructure required for the 2026 era of artificial intelligence. We are looking for a highly technical and visionary Senior AI Infrastructure Architect to lead our global engineering efforts. In this role, you will design the backbone of our next-generation AI ecosystem, ensuring scalability, security, and performance at a global scale.

As a key member of our elite engineering team, you will bridge the gap between cutting-edge AI research and robust, production-grade infrastructure. You will be responsible for architecting systems that are not only ready for today but are built to dominate the competitive landscape of 2026.

Responsibilities

  • Architect High-Performance Pipelines: Design and implement scalable inference architectures for next-generation Large Language Models (LLMs) and generative AI models.
  • Quantum-Ready Infrastructure: Evaluate and integrate emerging quantum computing protocols to future-proof our data processing capabilities.
  • Cloud-Native Optimization: Lead initiatives to optimize container orchestration (Kubernetes) and serverless functions for maximum cost-efficiency and throughput.
  • Security & Compliance: Enforce rigorous security standards for AI models, ensuring data privacy and mitigating adversarial attacks in real-time.
  • Technical Leadership: Mentor junior engineers and conduct architectural reviews to drive technical excellence across the organization.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
  • Experience: 7+ years of experience in software engineering with a focus on distributed systems and infrastructure.
  • Core Technologies: Proficiency in Python, Go, or Rust; deep experience with Kubernetes, Docker, and cloud providers (AWS/Azure/GCP).
  • AI/ML Knowledge: Strong understanding of machine learning lifecycle, MLOps, and model serving technologies.
  • Problem Solving: Proven track record of solving complex scalability and latency issues in high-demand environments.

Required Skills

Python Kubernetes Docker AWS MLOps Machine Learning Distributed Systems Cloud Architecture

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