Job Description
Are you ready to define the technological landscape of 2026? Quantum Horizon Systems is seeking a visionary Senior AI Infrastructure Architect to lead the development of scalable, high-performance systems designed for the future.
In this pivotal role, you will bridge the gap between cutting-edge AI research and robust engineering practices, ensuring our platforms are ready to handle the demands of the next generation of machine learning workloads. We are building the infrastructure that will power autonomous systems, advanced predictive analytics, and next-gen neural networks.
Why Join Our Visionary Team?
- Shape the Future: Play a direct role in defining the architectural standards for 2026 and beyond.
- High Impact: Work on projects that redefine industry standards in AI scalability and efficiency.
- Top-Tier Team: Collaborate with world-class engineers and researchers.
Core Responsibilities
- Architect and deploy scalable AI infrastructure pipelines optimized for 2026 workloads and future growth.
- Lead cloud migration strategies (AWS/Azure/GCP) to ensure high availability, security, and cost-efficiency.
- Collaborate closely with data science teams to translate research prototypes into production-grade, fault-tolerant services.
- Implement robust MLOps practices to streamline model training, deployment, and monitoring.
- Drive architectural decisions that align with long-term business goals and 2026 technological roadmaps.
Qualifications
- 10+ years of experience in software engineering, systems architecture, and infrastructure.
- Deep expertise in Python, TensorFlow, PyTorch, and Kubernetes.
- Proven track record of designing large-scale distributed systems that handle millions of requests.
- Experience with CI/CD pipelines, containerization, and serverless architectures.
- Strong understanding of data privacy, security, and compliance standards (SOC2, GDPR).
Responsibilities
- Architect and deploy scalable AI infrastructure pipelines optimized for 2026 workloads and future growth.
- Lead cloud migration strategies (AWS/Azure/GCP) to ensure high availability, security, and cost-efficiency.
- Collaborate closely with data science teams to translate research prototypes into production-grade, fault-tolerant services.
- Implement robust MLOps practices to streamline model training, deployment, and monitoring.
- Drive architectural decisions that align with long-term business goals and 2026 technological roadmaps.
Qualifications
- 10+ years of experience in software engineering, systems architecture, and infrastructure.
- Deep expertise in Python, TensorFlow, PyTorch, and Kubernetes.
- Proven track record of designing large-scale distributed systems that handle millions of requests.
- Experience with CI/CD pipelines, containerization, and serverless architectures.
- Strong understanding of data privacy, security, and compliance standards (SOC2, GDPR).