Job Description
We are building the technological foundation for the next decade. Nexus Horizon Labs is seeking a visionary Senior AI Infrastructure Architect to lead our initiatives leading into 2026.
In this pivotal role, you will engineer the core systems that power next-generation neural networks and decentralized AI agents. You will be responsible for optimizing compute resources, ensuring latency-free data throughput, and designing scalable architectures that can handle the complexity of autonomous systems. If you want to be at the cutting edge of what is possible in artificial intelligence and infrastructure, we want to hear from you.
Key Focus Areas:
- Scalable MLOps pipelines.
- Neural network optimization for edge computing.
- Quantum-ready software architecture.
Responsibilities
- Design and deploy high-performance distributed computing systems for training large-scale language models and generative AI agents.
- Optimize inference engines to reduce latency and improve throughput for real-time neural interfaces.
- Architect fault-tolerant Kubernetes clusters and microservices to ensure 99.99% uptime.
- Collaborate with data scientists to translate research prototypes into production-grade software.
- Implement rigorous security protocols and ethical AI compliance measures across all data pipelines.
- Lead technical strategy sessions to define the roadmap for AI infrastructure evolution.
- Conduct code reviews and mentor junior engineers in scalable backend engineering.
Qualifications
- Master’s degree in Computer Science, Electrical Engineering, or a related field (PhD preferred).
- 7+ years of experience in backend engineering with a focus on high-scale distributed systems.
- Proficiency in Python, C++, and Rust with deep understanding of memory management and performance optimization.
- Extensive experience with MLOps tools (MLflow, Kubeflow) and cloud platforms (AWS, GCP, Azure).
- Strong background in Deep Learning frameworks (PyTorch, TensorFlow, JAX).
- Experience with containerization (Docker, Kubernetes) and serverless computing.
- Familiarity with AI ethics, bias mitigation, and regulatory compliance (e.g., GDPR, CCPA).