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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect: 2026 Readiness

Nexus Future Systems
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
New
Live Update
4 Juli 2026
Deadline
4 Jul 2027

Job Description

Nexus Future Systems is defining the next era of artificial intelligence. As we accelerate toward the pivotal year of 2026, we are seeking a visionary Senior AI Architect to lead the engineering of our core infrastructure. You will be responsible for designing scalable, high-performance systems that bridge the gap between theoretical research and production-grade AI deployment.

This is a unique opportunity to shape the roadmap that will define how AI operates in a global, decentralized environment. If you are passionate about building the backbone of the future, we want to hear from you.

Why Join Us?

  • Work on cutting-edge Generative AI and Large Language Model (LLM) infrastructures.
  • Competitive salary and equity packages.
  • Flexible remote-first culture with a premium office in San Francisco.

Responsibilities

  • Architect end-to-end AI pipelines, from data ingestion to model deployment and serving.
  • Lead the technical strategy for "2026 Readiness," ensuring systems can handle exponential scaling.
  • Optimize deep learning models for latency, throughput, and energy efficiency.
  • Establish and enforce architectural standards for security, compliance, and scalability.
  • Collaborate with cross-functional teams of data scientists, researchers, and product managers.
  • Conduct code reviews and mentor junior engineers to foster a culture of technical excellence.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.
  • 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
  • Expert proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (MLflow, Kubeflow).
  • Deep experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
  • Strong understanding of distributed systems, microservices, and high-availability architectures.
  • Experience with Vector Databases and RAG (Retrieval-Augmented Generation) architectures.

Required Skills

Python Machine Learning Deep Learning Cloud Architecture MLOps Kubernetes TensorFlow PyTorch AI Strategy Distributed Systems

Ready to Take This Challenge?

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