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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Systems Architect (2026 Vision)

Quantum Leap Dynamics
San Francisco
Estimated Salary
USD 165.000 – USD 220.000
Live Update
27 Mei 2026
Deadline
27 Mei 2027

Job Description

We are on the precipice of a technological revolution, and Quantum Leap Dynamics is leading the charge into the year 2026. We are seeking a visionary Senior AI Systems Architect to design the neural infrastructures that will power the next generation of autonomous enterprise solutions.

In this role, you won't just be maintaining systems; you will be architecting the future. You will bridge the gap between cutting-edge machine learning models and scalable, real-world deployment. If you are obsessed with the future of technology and possess the technical prowess to build it, we want to hear from you.

Why Join Us?
• Work on projects that define the standard for 2026 and beyond.
• Competitive equity package and top-tier compensation.
• Collaborate with a world-class team of futurists and engineers.

Responsibilities

  • Architect and deploy scalable AI infrastructure capable of handling real-time data processing and autonomous decision-making loops.
  • Lead the design of seamless integration between legacy systems and next-gen generative AI models.
  • Define the technical roadmap for AI scalability, ensuring zero-latency performance and high availability.
  • Implement rigorous security protocols and ethical guidelines for autonomous AI agents.
  • Mentor a team of junior engineers and data scientists, fostering a culture of innovation and continuous learning.
  • Collaborate with product managers to translate futuristic concepts into concrete technical specifications.

Qualifications

  • 7+ years of experience in software architecture, with a specific focus on Artificial Intelligence and Machine Learning systems.
  • Deep proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
  • Proven experience designing microservices architectures using Docker, Kubernetes, and cloud platforms (AWS/GCP).
  • Experience with LLM fine-tuning, RAG (Retrieval-Augmented Generation), and vector databases.
  • Strong understanding of distributed systems, cloud-native principles, and system reliability engineering.
  • Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch AWS Kubernetes Docker Machine Learning System Architecture Cloud Computing AI Strategy

Ready to Take This Challenge?

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