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Information Technology 🏢 Full Time ⭐️ Verified

AI Systems Architect

Nexus Horizon
San Francisco
Estimated Salary
USD 165.000 – USD 230.000
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Are you ready to architect the digital landscape of 2026 and beyond? Nexus Horizon is seeking a visionary AI Systems Architect to lead our next-generation infrastructure projects. In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable, production-ready systems designed for the future.

We are not just looking for a coder; we need a strategist who understands the trajectory of technology and can build resilient architectures for the decade ahead.

Responsibilities

  • Architect Future-Proof Systems: Design robust, scalable AI infrastructures capable of handling evolving data models and complex neural networks.
  • Lead Technical Vision: Define the technical roadmap for 2026, integrating cutting-edge Generative AI and Agentic workflows.
  • Optimize Performance: Implement advanced optimization techniques to ensure low-latency inference and high-throughput processing.
  • Cloud & Edge Integration: Oversee the deployment of AI models across distributed cloud environments and edge computing devices.
  • Collaborate with R&D: Work closely with researchers to translate experimental models into production-grade software.

Qualifications

  • Proven Expertise: 7+ years of experience in software architecture, with at least 3 years specifically focused on AI/ML infrastructure.
  • Technical Stack: Deep proficiency in Python, TensorFlow, PyTorch, and distributed systems.
  • Cloud Mastery: Strong experience with AWS, Google Cloud Platform (GCP), or Azure, including Kubernetes and serverless architectures.
  • Future-Forward Mindset: Demonstrated ability to anticipate emerging tech trends (e.g., Quantum AI, Autonomous Agents) and apply them practically.
  • Leadership: Experience leading cross-functional teams of engineers and data scientists.

Required Skills

Python TensorFlow PyTorch AWS GCP Kubernetes Machine Learning System Design Deep Learning Cloud Architecture

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