Job Description
Shape the Future of Intelligence. Nexus Future Systems is pioneering the infrastructure required for the 2026 technological horizon. We are seeking a visionary Principal AI Architect to lead the deployment of next-generation generative models, neuromorphic computing systems, and quantum-ready data pipelines. If you are obsessed with scalability, efficiency, and the bleeding edge of AI, this is your opportunity to define the standard for the industry.
As a key leader in our engineering division, you will bridge the gap between theoretical AI research and production-grade infrastructure. You will architect resilient systems capable of handling petabyte-scale data streams and real-time inference at global scale.
Responsibilities
- Architect Next-Gen Infrastructure: Design and implement scalable distributed systems for 2026-era AI workloads, including LLM orchestration and edge computing integration.
- Neuromorphic Optimization: Oversee the deployment of hardware-accelerated neural networks to maximize inference speed and energy efficiency.
- Quantum-Ready Data Pipelines: Build and maintain hybrid cloud architectures that seamlessly transition between classical and quantum computing environments.
- Security & Governance: Implement rigorous AI governance frameworks to ensure data privacy, compliance (GDPR/CCPA), and ethical AI usage.
- Technical Leadership: Mentor senior engineers and architects, conducting code reviews, and driving technical strategy across cross-functional teams.
- Performance Tuning: Continuously optimize model latency and throughput, reducing operational costs while increasing system reliability.
Qualifications
- Experience: 7+ years of experience in software engineering, DevOps, or Systems Architecture with a focus on Artificial Intelligence.
- Core Technologies: Deep proficiency in Python, C++, Rust, and containerization technologies (Docker, Kubernetes).
- Cloud Mastery: Extensive experience architecting on AWS, GCP, or Azure, specifically utilizing serverless and GPU-accelerated instances.
- AI Frameworks: Hands-on experience with PyTorch, TensorFlow, or JAX, and familiarity with MLOps tools (MLflow, Kubeflow).
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.