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Senior AI Architect: 2026 Roadmap | San Francisco, CA

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
14 Mei 2026
Deadline
14 Mei 2027



Job Description

We are seeking a visionary Senior AI Architect to spearhead our strategic roadmap for the year 2026. As technology accelerates, we need a leader who can bridge the gap between current capabilities and the future of artificial general intelligence. You will be responsible for designing scalable, secure, and high-performance AI systems that will define the next decade of innovation.

Why Join Us?
This is a high-impact role where you will have the autonomy to shape the technical direction of our core products. We offer competitive equity packages, a remote-first culture with a hub in San Francisco, and the chance to work on cutting-edge algorithms.

Responsibilities

  • Architect Future-Proof Systems: Design and implement robust AI infrastructure capable of scaling to petabyte-level data sets for 2026 demands.
  • Lead Research & Development: Oversee the R&D team in exploring emerging paradigms such as Neural Symbolic AI and Agentic workflows.
  • Optimization Strategy: Drive the optimization of model inference speeds and reduce latency in real-time applications using edge computing and quantization.
  • Technical Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
  • Security & Compliance: Implement rigorous security protocols to ensure data privacy and model integrity in decentralized networks.
  • Strategic Planning: Translate business goals into technical roadmaps, defining milestones for the 2026 release cycle.

Qualifications

  • Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field.
  • Experience: 8+ years of experience in software engineering and machine learning, with at least 3 years in a leadership or architect role.
  • Core Skills: Deep expertise in Python, PyTorch, TensorFlow, and CUDA.
  • Knowledge: Proven experience with Large Language Models (LLMs), fine-tuning, and RAG (Retrieval-Augmented Generation).
  • Cloud Proficiency: Strong experience with AWS, Azure, or GCP, specifically in running ML workloads.
  • Problem Solving: Exceptional ability to solve complex technical problems and make architectural decisions under pressure.

Required Skills

Python PyTorch TensorFlow Machine Learning AI Architecture Cloud Computing (AWS/Azure) NLP Deep Learning CUDA Kubernetes

Ready to Take This Challenge?

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