Job Description
Join the Architects of Tomorrow
At Apex Future Systems, we are not just building the software of today; we are architecting the digital infrastructure for 2026 and beyond. We are seeking a visionary AI Infrastructure Architect to lead our core compute strategy, ensuring our platforms can handle the exponential growth of generative AI and deep learning models. You will define the technical roadmap that powers our next-generation products and ensures scalability, security, and performance at a global scale.
In this pivotal role, you will bridge the gap between cutting-edge research and robust production engineering. You will work directly with our Chief Technology Officer and a world-class team of ML engineers to design systems that are resilient, efficient, and ready for the future of technology.
Responsibilities
- Strategic Infrastructure Design: Define and implement the architectural vision for scalable AI workloads, focusing on high availability and fault tolerance for the 2026 roadmap.
- Cloud & Kubernetes Leadership: Oversee the deployment and optimization of Kubernetes clusters on AWS and GCP, managing resource allocation for GPU-intensive training and inference tasks.
- Performance Optimization: Analyze system bottlenecks and implement high-performance computing (HPC) solutions to accelerate model training times and reduce operational costs.
- DevOps & Automation: Build and maintain CI/CD pipelines and automated infrastructure-as-code (IaC) using Terraform and Ansible to ensure rapid, safe deployment cycles.
- Security & Compliance: Enforce rigorous security protocols and data governance policies to protect intellectual property and ensure compliance with industry standards.
- Cross-Functional Collaboration: Partner with data scientists and product managers to translate business requirements into scalable technical solutions.
Qualifications
- Experience: 8+ years of experience in Systems Engineering, DevOps, or Cloud Architecture, with at least 3 years focused on AI/ML infrastructure.
- Technical Stack: Deep expertise in Kubernetes, Docker, Python, and Linux. Experience with AWS (EC2, EKS, SageMaker) or GCP (GKE, AI Platform) is required.
- AI Knowledge: Strong understanding of machine learning workflows, GPU clusters, and data pipelines (e.g., Apache Spark, Airflow).
- Soft Skills: Exceptional problem-solving skills, excellent communication abilities, and a passion for mentoring junior engineers.
- Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s preferred).
- Future-Ready Mindset: Proven track record of anticipating industry trends and implementing forward-thinking solutions.