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Future Systems Architect (2026)

Aether Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

We are defining the future of technology. At Aether Dynamics, we are on a mission to architect the infrastructure for the year 2026 and beyond. We are looking for a visionary Future Systems Architect to lead the development of next-generation autonomous frameworks and quantum-ready AI ecosystems.

In this high-impact role, you will not just write code; you will shape the foundational logic of tomorrow's intelligent systems. You will bridge the gap between theoretical AI advancements and scalable, practical engineering solutions.

Responsibilities

  • Design and deploy scalable, fault-tolerant distributed systems capable of processing exabyte-scale data streams.
  • Lead the architectural roadmap for the 2026 release, integrating generative AI models with real-time edge computing.
  • Collaborate with cross-functional teams to define best practices for model explainability and ethical AI.
  • Optimize neural network architectures for quantum computing environments and next-gen hardware.
  • Drive technical innovation in Natural Language Processing (NLP) and Computer Vision pipelines.
  • Provide strategic guidance to engineering teams, fostering a culture of technical excellence and rapid iteration.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
  • 10+ years of progressive experience in software engineering, with at least 5 years in AI architecture.
  • Deep expertise in Python, TensorFlow, PyTorch, and distributed systems design.
  • Experience with quantum computing frameworks (e.g., Cirq, Qiskit) and their application to classical ML problems.
  • Strong understanding of cloud infrastructure (AWS, GCP, Azure) and containerization (Kubernetes, Docker).
  • Proven track record of leading high-performance teams through complex technical transformations.

Required Skills

Python Machine Learning TensorFlow PyTorch Distributed Systems Cloud Architecture Quantum Computing System Design NLP Docker Kubernetes

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