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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect - Project 2026

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Join the Vanguard of Innovation

Nexus Future Systems is pioneering the Project 2026 initiative, a groundbreaking effort to integrate quantum-ready AI into global infrastructure. We are seeking a visionary Senior AI Architect to lead the architectural design of next-generation machine learning models and autonomous systems.

In this role, you won't just write code; you will define the very standards of the digital future. You will bridge the gap between theoretical research and production-grade deployment, ensuring our systems are scalable, secure, and ahead of the curve.

If you are passionate about solving complex problems at the intersection of AI, quantum computing, and cloud infrastructure, we want to hear from you.

Responsibilities

  • Architectural Leadership: Design and oversee the implementation of the core AI infrastructure for Project 2026, ensuring high availability and fault tolerance.
  • Strategic Roadmap: Translate business objectives into technical strategies, defining the technical vision for the 2026 release cycle.
  • Model Optimization: Lead the research and deployment of Large Language Models (LLMs) and generative AI agents, optimizing for speed and accuracy.
  • Talent Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
  • Cross-Functional Collaboration: Partner with product managers, security teams, and stakeholders to deliver robust technical solutions.
  • Future-Proofing: Evaluate emerging technologies (e.g., neuromorphic computing) to integrate into our current stack.

Qualifications

  • Experience: 8+ years of software engineering experience with at least 3 years in AI/ML architecture and system design.
  • Technical Stack: Proficiency in Python, TensorFlow, PyTorch, and distributed systems.
  • Cloud Expertise: Deep experience with AWS, GCP, or Azure, specifically in deploying ML workloads.
  • System Design: Proven ability to design scalable microservices and containerized applications using Docker and Kubernetes.
  • Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning System Design Cloud Architecture (AWS/GCP) Kubernetes Docker TensorFlow PyTorch Large Language Models SQL Agile Methodologies

Ready to Take This Challenge?

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