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Senior AI Architect (2026 Vision) - San Francisco, CA

Zenith Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join the Architects of Tomorrow.

Zenith Future Labs is pioneering the next generation of autonomous systems and generative intelligence. We are seeking a visionary Senior AI Architect to lead our 2026 product roadmap, focusing on scalable, secure, and ethical AI infrastructures. If you are passionate about defining the technological landscape of the future, we want to hear from you.


Why Join Us?
We offer a competitive compensation package, equity opportunities, and a culture that prioritizes innovation and deep technical craftsmanship.

Responsibilities

  • Architect Next-Gen AI Systems: Design and implement scalable machine learning pipelines and large language model (LLM) integrations tailored for the 2026 market.
  • Lead Technical Vision: Define the long-term technical strategy and architectural standards for our core AI products, ensuring alignment with business goals.
  • Optimize Performance: Drive performance engineering to ensure low-latency inference and efficient model training on distributed cloud environments.
  • Research & Development: Stay ahead of the curve by exploring emerging AI paradigms, such as Agentic workflows and Multimodal learning.
  • Code Review & Mentorship: Foster a high-performance engineering culture by conducting rigorous code reviews and mentoring junior data scientists and engineers.
  • Security & Compliance: Implement robust security protocols and ensure all AI systems adhere to strict data privacy regulations.

Qualifications

  • Education: M.S. or Ph.D. 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 senior architectural role.
  • Core Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Apache Spark, Ray).
  • AI Expertise: Deep understanding of Transformer architectures, NLP, and fine-tuning techniques for LLMs.
  • Cloud Native: Extensive experience deploying and managing models on AWS, GCP, or Azure using containerization (Docker/Kubernetes).
  • Problem Solving: Proven ability to tackle complex, unstructured problems and deliver robust, production-ready solutions.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Large Language Models LLM MLOps Kubernetes Docker AWS GCP Cloud Architecture System Design

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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