Job Description
We are at the forefront of technological evolution, preparing our infrastructure for the demands of the year 2026 and beyond. Horizon Systems is seeking a visionary Future Tech Architect to lead our initiative in designing scalable, quantum-ready AI ecosystems.
In this pivotal role, you will bridge the gap between theoretical future-state technologies and current engineering realities. You will define the architectural standards that will support our next generation of autonomous agents and generative AI models. If you are passionate about the next decade of computing and possess the technical prowess to build systems that last, we want to hear from you.
Why Join Us?
- Work on the cutting edge of AI and quantum computing integration.
- Competitive compensation and equity package.
- Flexible remote-first culture with a focus on innovation.
Responsibilities
- Define the 2026 Roadmap: Collaborate with stakeholders to define long-term technical strategies for AI infrastructure, focusing on scalability and sustainability.
- Architect Scalable Systems: Design and implement microservices architectures capable of handling high-throughput generative AI workloads and quantum data processing.
- Optimize Performance: Implement advanced caching strategies, load balancing, and edge computing solutions to minimize latency for global users.
- Lead Technical Innovation: Evaluate emerging technologies (e.g., neuromorphic computing, advanced LLMs) and prototype viable integration paths.
- Code Reviews & Mentorship: Lead a team of senior engineers, conducting rigorous code reviews to ensure security and best practices.
- Disaster Recovery Planning: Develop robust failover systems and data redundancy protocols to ensure business continuity in a decentralized environment.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Physics, or a related field; PhD preferred.
- Experience: 8+ years of experience in software architecture, with at least 3 years specifically focused on AI/ML infrastructure.
- Technical Skills: Deep proficiency in Python, Rust, or Go; experience with Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
- AI Knowledge: Strong understanding of machine learning frameworks (PyTorch, TensorFlow) and the ability to design systems that feed and train these models efficiently.
- Problem Solving: Exceptional ability to solve complex, ambiguous problems with innovative, scalable solutions.
- Soft Skills: Excellent communication skills with the ability to translate technical concepts for non-technical leadership.