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Information Technology 🏢 Full Time ⭐️ Verified

AI Infrastructure Architect (2026 Vision)

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

The Opportunity: Nexus Future Systems is pioneering the foundational infrastructure for the next decade. We are seeking a visionary AI Infrastructure Architect (2026 Vision) to lead our engineering team in San Francisco. In this pivotal role, you will bridge the gap between cutting-edge artificial intelligence and resilient, scalable cloud architecture. You will be instrumental in architecting systems that are not only efficient today but are built to lead the industry into 2026 and beyond.

Why Join Us? We offer a competitive compensation package, equity opportunities, and the chance to work on projects that define the future of human-machine interaction.

Key Responsibilities:

Responsibilities

  • Architect Next-Gen AI Systems: Design and implement scalable cloud-native infrastructure tailored for large-scale AI and machine learning workloads.
  • Lead Technical Roadmap (2026): Define and execute the technical strategy for infrastructure evolution, ensuring readiness for future AI paradigms.
  • Optimize Performance: Enhance system throughput, latency, and cost-efficiency for real-time AI inference and training clusters.
  • Cloud & DevOps Integration: Oversee the deployment of Kubernetes clusters and CI/CD pipelines using Terraform and Docker on AWS/Azure.
  • Security & Compliance: Enforce rigorous security protocols and data governance standards to protect proprietary AI models.
  • Cross-Functional Collaboration: Partner with data scientists and software engineers to translate business requirements into robust architectural solutions.
  • Team Mentorship: Cultivate a culture of innovation, providing technical guidance and mentorship to junior architects and engineers.

Qualifications

  • Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s degree preferred).
  • Experience: 7+ years of experience in software engineering, with at least 4 years specifically in AI infrastructure or cloud architecture.
  • Technical Stack: Proficiency in Python, Kubernetes, Docker, Terraform, and major cloud providers (AWS/GCP/Azure).
  • AI/ML Knowledge: Deep understanding of machine learning model lifecycle, MLOps, and data pipeline architecture.
  • Leadership: Proven track record of leading technical teams and managing complex infrastructure projects.
  • Problem Solving: Exceptional analytical skills with a focus on scalability and fault tolerance.
  • Communication: Excellent verbal and written communication skills, capable of articulating complex technical concepts to stakeholders.

Required Skills

Kubernetes Docker Python AWS Azure Machine Learning MLOps Cloud Architecture Terraform CI/CD Machine Learning Engineering

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