Job Description
Are you ready to engineer the infrastructure of tomorrow? Horizon 2026 Technologies is seeking a visionary Future-Ready AI Architect to lead our R&D division. We are building the core systems that will power the digital landscape of 2026 and beyond, focusing on scalable AI, quantum computing integration, and sustainable cloud infrastructure.
In this role, you won't just maintain systems; you will define their evolution. You will bridge the gap between theoretical future tech and practical implementation, ensuring our platforms are resilient, intelligent, and future-proof.
Why join us? We offer a competitive package, stock options, and the freedom to experiment with bleeding-edge technologies in a collaborative, high-performance environment.
Responsibilities
- Architect Future-Proof Systems: Design and oversee the development of scalable, high-availability infrastructure specifically engineered to meet the performance and security standards of 2026.
- Pilot AI Integration: Lead the integration of generative AI and machine learning models into core product architectures to enhance automation and user experience.
- Quantum Readiness: Assess and implement transitional strategies to prepare our current cloud environments for future quantum computing capabilities.
- Cloud Modernization: Spearhead migration strategies to next-gen cloud environments (e.g., Serverless, Edge Computing) ensuring zero-latency operations.
- Security & Compliance: Implement advanced security protocols (Zero Trust architecture) to protect data integrity against evolving cyber threats.
- Technical Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Experience: 8+ years of experience in software architecture, cloud engineering, or systems design.
- Core Skills: Proficiency in Python, Go, or Rust, with deep understanding of distributed systems.
- Cloud Mastery: Expert-level certification (AWS/Azure/GCP) and hands-on experience with containerization (Docker/Kubernetes) and serverless computing.
- AI Knowledge: Strong background in Neural Networks, NLP, and Large Language Model (LLM) integration.
- Problem Solving: Proven track record of solving complex architectural challenges and optimizing legacy systems.
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.