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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI Architect - The 2026 Initiative

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

Job Description

We are building the future of technology, and we need a visionary to lead the 2026 Initiative. Nexus Future Labs is seeking a world-class Lead AI Architect to design scalable, ground-breaking AI systems that will define the next decade of intelligent computing.

In this pivotal role, you will bridge the gap between theoretical AI research and production-grade engineering. You will own the architectural vision for our flagship 2026 platform, ensuring robustness, scalability, and performance at the edge.

If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.

Responsibilities

  • Architectural Leadership: Define the end-to-end technical architecture for the 2026 AI ecosystem, ensuring alignment with business goals and future scalability.
  • System Design: Design and implement complex distributed systems, leveraging cloud-native technologies and edge computing paradigms.
  • Team Mentorship: Lead a high-performing engineering team, providing technical guidance, code reviews, and fostering a culture of innovation.
  • Roadmap Execution: Collaborate with product and research teams to translate strategic 2026 goals into concrete technical roadmaps.
  • Performance Optimization: Continuously monitor and optimize system performance, latency, and cost-efficiency.
  • Technical Strategy: Stay ahead of industry trends in Generative AI and Neural Architecture Search to keep our technology stack cutting-edge.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field; PhD preferred.
  • Experience: 8+ years of software engineering experience with at least 4 years in a lead architectural role.
  • Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with distributed training frameworks.
  • Cloud Mastery: Proficiency in designing systems on AWS, Google Cloud Platform, or Azure.
  • Problem Solving: Proven track record of solving complex technical challenges in high-scale environments.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Cloud Architecture Distributed Systems Machine Learning System Design AWS GCP Leadership

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