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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Systems Architect

Nexus Future Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

Architect the Future of Intelligence. At Nexus Future Labs, we are not just building software; we are defining the era of 2026 and beyond. We are seeking a visionary Senior AI Systems Architect to lead the design and deployment of next-generation artificial intelligence infrastructure. In this role, you will bridge the gap between theoretical AI research and scalable production systems.

What You'll Do:

We are looking for a problem-solver who thrives in ambiguity. You will be responsible for the end-to-end lifecycle of our AI platforms, ensuring they are robust, secure, and ready for the demands of tomorrow.

Responsibilities

  • Design Scalable Architectures: Design and implement high-performance distributed systems capable of handling petabyte-scale data and real-time inference.
  • Lead R&D Strategy: Identify and evaluate emerging technologies (e.g., Quantum-ready algorithms, Edge AI) to drive our 2026 roadmap.
  • Optimize Model Efficiency: Work closely with ML engineers to reduce model latency and resource overhead without sacrificing accuracy.
  • Ensure Security & Compliance: Implement best-in-class security protocols and data governance frameworks to protect sensitive AI models.
  • Technical Mentorship: Mentor a high-performing team of engineers, fostering a culture of technical excellence and continuous innovation.
  • Cross-Functional Collaboration: Partner with Product Managers and Data Scientists to translate business requirements into technical blueprints.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field (PhD preferred).
  • Experience: 5+ years of experience in software engineering with a strong focus on Machine Learning and Artificial Intelligence systems.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
  • Cloud Expertise: Deep experience with AWS, GCP, or Azure architecture and serverless computing.
  • Problem Solving: Demonstrated ability to architect complex systems that are fault-tolerant and scalable.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning System Design Cloud Computing Kubernetes PyTorch TensorFlow AWS GCP Data Engineering

Ready to Take This Challenge?

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