Job Description
Are you ready to shape the future of technology? Nexus Horizon is seeking a visionary Senior AI Infrastructure Architect to lead our mission into the 2026 era. We are building the foundational systems that will power the next decade of human-machine collaboration.
In this role, you will bridge the gap between cutting-edge AI research and scalable, robust infrastructure. You will define the architectural standards that ensure our platforms remain resilient, secure, and infinitely scalable as we approach our 2026 strategic goals.
Why Join Nexus Horizon?
- Impact: Directly influence the core architecture of systems used by millions worldwide.
- Future-Proof: Work on technologies and paradigms designed for the 2026 and beyond.
- Compensation: Competitive salary and equity package reflecting your seniority.
Join us in defining the blueprint for the future.
Responsibilities
- Architectural Strategy: Design and implement high-availability, distributed AI infrastructure capable of processing petabyte-scale datasets.
- System Optimization: Lead initiatives to optimize latency, throughput, and cost-efficiency across our global cloud ecosystem.
- Technology Roadmap: Identify and evaluate emerging technologies (e.g., quantum-ready architectures, edge computing) to prepare our stack for 2026 deployment.
- Cross-Functional Leadership: Collaborate with data scientists, ML engineers, and security teams to ensure seamless integration of new AI models.
- Code Review & Mentorship: Establish rigorous code quality standards and mentor a team of high-performing infrastructure engineers.
- Disaster Recovery: Develop and maintain comprehensive disaster recovery plans to ensure business continuity.
Qualifications
- Experience: 8+ years of experience in software architecture, with a minimum of 4 years specifically in AI/ML infrastructure.
- Core Tech Stack: Deep proficiency in Python, Go, Rust, Kubernetes, Docker, and Terraform.
- Cloud Expertise: Proven track record architecting solutions on AWS, GCP, or Azure.
- AI Integration: Experience integrating LLMs, neural networks, and MLOps pipelines into production environments.
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Soft Skills: Exceptional problem-solving abilities and the ability to communicate complex technical concepts to non-technical stakeholders.