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Senior AI Architect: The 2026 Initiative

FutureScale Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Are you ready to build the future?

FutureScale Technologies is leading the 2026 Initiative, a groundbreaking research and development project aimed at redefining the capabilities of Generative AI and autonomous agents. We are seeking a visionary Senior AI Architect to join our elite engineering team in San Francisco.

In this pivotal role, you will be responsible for designing the architectural foundation of our next-generation AI ecosystem. You will bridge the gap between theoretical research and production-grade engineering, ensuring our systems are scalable, secure, and revolutionary. If you thrive in a fast-paced, high-impact environment and are passionate about the technologies that will shape the year 2026 and beyond, we want you on our team.

Responsibilities

  • Design and implement scalable, high-performance AI architectures for the 2026 product roadmap.
  • Lead the optimization of Large Language Models (LLMs) and Transformer networks for real-time inference.
  • Collaborate with cross-functional teams to integrate AI capabilities into complex software solutions.
  • Establish best practices for data pipelines, model training, and deployment in cloud environments.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
  • Conduct rigorous code reviews and technical architecture assessments to ensure system integrity.
  • Stay at the forefront of AI research, identifying emerging trends and technologies to apply to our projects.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
  • 8+ years of experience in software engineering, with at least 4 years specializing in AI/ML.
  • Expert proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
  • Proven experience deploying and scaling LLMs and generative models in production environments.
  • Strong background in distributed systems, cloud architecture (AWS/GCP), and MLOps.
  • Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
  • Exceptional problem-solving skills and the ability to communicate complex technical concepts clearly.

Required Skills

Python PyTorch TensorFlow LLMs Machine Learning Deep Learning Distributed Systems AWS MLOps Data Structures Algorithms

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