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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI Infrastructure Engineer

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

Job Description

Welcome to Nexus 2026. We are building the foundational infrastructure for the next era of autonomous intelligence. Our mission is to solve the most complex scalability and efficiency challenges in Generative AI and Quantum-ready computing. We are looking for a Lead AI Infrastructure Engineer to join our elite team in San Francisco.

In this role, you will be responsible for architecting the backbone of our systems, ensuring they are not only robust and secure but also capable of handling the exponential data growth predicted for 2026 and beyond. You will work at the intersection of hardware optimization and software engineering to deliver cutting-edge solutions.

Why join Nexus 2026?
We offer competitive equity packages, top-tier health benefits, and a culture that prioritizes innovation and autonomy. You will have the opportunity to shape the future of technology while working with industry leaders in AI and cloud infrastructure.

Responsibilities

  • Design and implement scalable, fault-tolerant infrastructure for high-performance AI workloads.
  • Optimize deep learning pipelines and model serving architectures for reduced latency.
  • Collaborate with research teams to translate theoretical models into production-ready systems.
  • Implement and manage CI/CD pipelines using Kubernetes and container orchestration.
  • Ensure cloud security compliance and data privacy standards across all global regions.
  • Conduct performance tuning and capacity planning for future growth.

Qualifications

  • 8+ years of experience in software engineering, with at least 3 years in AI infrastructure or MLOps.
  • Strong proficiency in Python, Go, or Rust.
  • Deep understanding of containerization technologies (Docker, Kubernetes).
  • Experience with cloud platforms (AWS, GCP, or Azure) and serverless architectures.
  • Experience with distributed systems, message queues, and high-throughput data processing.
  • Excellent problem-solving skills and the ability to mentor junior engineers.

Required Skills

Python Kubernetes AWS MLOps Deep Learning System Architecture Docker CI/CD Cloud Computing

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