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AI Systems Architect (2026 Vision)

QuantumLeap Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
18 Mei 2026
Deadline
18 Mei 2027

Job Description

Join QuantumLeap Dynamics to architect the future of AI-driven systems in 2026. We're pioneering next-generation neural networks and quantum-entangled computing architectures that will redefine technological boundaries. As our AI Systems Architect, you'll lead the design and implementation of scalable, self-optimizing infrastructure that powers our autonomous ecosystems. This is your chance to shape how humanity interacts with intelligent systems in the coming decade.

What you'll achieve:

  • Design fault-tolerant AI systems with 99.999% uptime
  • Integrate quantum computing interfaces with classical neural networks
  • Develop adaptive security protocols for AGI-era threats
  • Lead cross-disciplinary teams of robotics, blockchain, and bio-AI specialists
  • Architect ethical governance frameworks for autonomous decision-making

Responsibilities

  • Architect next-gen AI systems with 10+ million parameter models
  • Design hybrid quantum-classical computing infrastructures
  • Implement self-healing network topologies for distributed AI agents
  • Create ethical compliance frameworks for autonomous systems
  • Lead migration from legacy architectures to 2026 standards
  • Develop neural-symbolic fusion architectures
  • Optimize systems for edge-to-cloud AI orchestration
  • Establish protocols for human-AI symbiotic interfaces

Qualifications

  • 10+ years in AI/ML systems architecture
  • Expertise in quantum computing interfaces (Qiskit, Cirq)
  • PhD in Computer Science or equivalent research experience
  • Published work on neural-symbolic integration
  • Proficiency in distributed systems (Kubernetes, Mesos)
  • Deep learning framework mastery (PyTorch, TensorFlow 2.x)
  • Experience with federated learning architectures
  • Knowledge of AGI safety frameworks (ALFA, MIRI)

Required Skills

AI Architecture Quantum Computing Neural Networks Distributed Systems Ethics in AI Machine Learning Robotics Blockchain

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