Job Description
Join the Architects of Tomorrow
Are you ready to define the technology landscape of 2026? Nexus 2026 is seeking a visionary Senior AI Systems Architect to lead our next-generation infrastructure. In this pivotal role, you will design scalable, high-performance AI systems that will power our products for years to come. If you are passionate about pushing the boundaries of machine learning and building robust cloud-native architectures, we want to hear from you.
Why Join Nexus 2026?
We are not just building software; we are engineering the future. Our team thrives on innovation, collaboration, and the pursuit of excellence. As a Senior AI Systems Architect, you will have the autonomy to shape our technical direction and mentor a team of brilliant engineers.
Responsibilities
- Architect Scalable AI Solutions: Design and implement robust, scalable AI and machine learning systems capable of handling massive data volumes and complex computations.
- Lead R&D Initiatives: Spearhead research and development projects to integrate cutting-edge technologies (e.g., Large Language Models, Edge AI) into our production environment.
- Optimize System Performance: Continuously monitor, analyze, and optimize system latency, throughput, and resource utilization to ensure 99.99% uptime.
- Cloud Infrastructure Management: Define and manage cloud infrastructure strategies on AWS or GCP, ensuring security best practices and cost-efficiency.
- Mentorship & Technical Leadership: Guide junior engineers and data scientists, conducting code reviews, architecture reviews, and technical training sessions.
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and stakeholders to translate business requirements into technical solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, with a minimum of 3 years specifically in AI/ML systems architecture.
- Technical Skills: Deep proficiency in Python, TensorFlow, PyTorch, and modern ML frameworks.
- Cloud Expertise: Extensive experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
- System Design: Strong understanding of distributed systems, microservices architecture, and database technologies (SQL/NoSQL).
- Problem Solving: Exceptional ability to troubleshoot complex technical issues and make data-driven architectural decisions.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.