Job Description
Architecting the Future of Intelligence.
Nexus Horizon Labs is seeking a visionary Future Systems Architect to lead the development of next-generation AI and Edge Computing infrastructure. In this pivotal role, you will bridge the gap between theoretical AI models and scalable, real-world deployment, ensuring our systems remain at the forefront of the 2026 technological landscape.
We are not just building software; we are defining the operational standard for tomorrow. If you possess a deep understanding of distributed systems and a passion for pushing the boundaries of what is possible, we want to hear from you.
Responsibilities
- Lead System Architecture: Design and implement resilient, scalable distributed systems that integrate advanced Machine Learning models with edge devices.
- R&D Leadership: Drive research and development initiatives focused on predictive analytics, quantum-resistant encryption, and autonomous infrastructure management.
- Cross-Functional Collaboration: Partner with data scientists, software engineers, and product managers to translate complex technical requirements into robust engineering solutions.
- Performance Optimization: Continuously monitor system health and optimize data pipelines to ensure sub-millisecond latency in high-throughput environments.
- Security Implementation: Establish and enforce best-in-class security protocols and compliance standards for all future-facing data architectures.
- Mentorship: Cultivate a high-performance engineering culture by mentoring junior architects and fostering technical excellence.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field (PhD preferred).
- Experience: 8+ years of experience in systems architecture, with at least 3 years leading teams in cloud-native environments.
- Technical Stack: Proficiency in Python, Go, or Rust; extensive experience with Kubernetes, Docker, and microservices; deep knowledge of AWS, Azure, or Google Cloud Platform.
- AI Integration: Strong understanding of integrating AI/ML models into production systems, particularly experience with TensorFlow, PyTorch, or ONNX.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in high-stakes environments.
- Soft Skills: Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.