Job Description
We are at the precipice of a technological revolution. Nexus Horizon Systems is seeking a visionary Lead Architect for the 2026 Initiative to design the scalable, resilient, and intelligent infrastructure of tomorrow. If you are passionate about pushing the boundaries of what is possible with Artificial Intelligence, Cloud Native architecture, and real-time data processing, we want to meet you.
In this pivotal role, you will be responsible for the end-to-end architecture of our flagship '2026' product suite, ensuring seamless integration of next-gen AI models with legacy enterprise systems. You will lead a team of elite engineers, define technical roadmaps, and ensure our solutions are secure, efficient, and future-proof.
Join us in building the digital backbone of the future.
Responsibilities
- Architectural Vision: Design and implement a scalable, microservices-based architecture tailored for high-volume AI processing and real-time analytics.
- Technology Strategy: Evaluate and integrate emerging technologies (e.g., Quantum-ready algorithms, Edge AI) into the 2026 core stack.
- Team Leadership: Mentor senior engineers and architects, conducting code reviews, technical architecture reviews, and fostering a culture of innovation.
- System Optimization: Drive performance tuning, security hardening, and cost optimization for cloud infrastructure (AWS/Azure/GCP).
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and stakeholders to translate business requirements into technical blueprints.
- Disaster Recovery: Develop and maintain robust disaster recovery plans and high availability strategies to ensure business continuity.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (PhD preferred).
- Experience: 10+ years of experience in software architecture, with at least 5 years in a Lead Architect or Principal Engineer role.
- Core Skills: Deep expertise in Python, Go, or Rust, with proven experience in designing distributed systems.
- Cloud Mastery: Extensive hands-on experience with major cloud providers (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker).
- AI/ML Integration: Strong understanding of integrating ML models into production environments and data pipelines.
- Soft Skills: Exceptional communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.