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Information Technology 🏢 Full Time ⭐️ Verified

AI Infrastructure Architect 2026

QuantumLeap Systems
Austin
Estimated Salary
USD 185.000 – USD 225.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

Join QuantumLeap Systems at the forefront of technological evolution as we pioneer AI infrastructure for 2026. We seek a visionary AI Infrastructure Architect to design and implement next-generation systems that will power the next decade of innovation. This role demands expertise in cutting-edge AI frameworks, distributed computing, and scalable architecture to solve humanity's most complex challenges.

In this pivotal position, you'll collaborate with world-class researchers and engineers to build the foundational infrastructure for tomorrow's AI applications. Your work will directly influence how global enterprises deploy machine learning at scale, ensuring performance, security, and sustainability in an era of exponential data growth.

QuantumLeap Systems offers a competitive compensation package, flexible work arrangements, and unparalleled opportunities to shape the future of artificial intelligence. If you're passionate about building systems that matter, we invite you to apply.

Responsibilities

  • Design and implement scalable AI infrastructure supporting 10M+ concurrent models
  • Architect hybrid cloud/on-premise solutions for quantum-class AI workloads
  • Optimize GPU/TPU clusters for real-time inference at petabyte scale
  • Develop MLOps pipelines for automated model lifecycle management
  • Implement security frameworks for federated learning systems
  • Lead migration from legacy systems to 2026-ready AI infrastructure
  • Collaborate with research teams to prototype next-gen AI accelerators

Qualifications

  • 8+ years in distributed systems architecture with 5+ years in AI/ML infrastructure
  • Expertise in Kubernetes, Terraform, and cloud-native AI orchestration
  • Deep knowledge of GPU/TPU optimization and high-performance computing
  • Experience with federated learning and secure multi-party computation
  • Proven track record of designing systems for exascale workloads
  • Strong background in MLOps and CI/CD for AI pipelines
  • PhD or equivalent in Computer Science or related field preferred

Required Skills

AI Infrastructure Distributed Systems Kubernetes MLOps GPU Optimization Cloud Architecture Terraform Quantum Computing High-Performance Computing

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