Job Description
We are on the precipice of a new era. At Nexus Horizon, our mission is to architect the infrastructure for the year 2026 and beyond. We are seeking a visionary Future Systems Architect to lead our core engineering team in developing scalable, high-performance systems designed for the next decade of technological evolution.
You will not just be writing code; you will be defining the blueprint for how humanity interacts with advanced technology. From orbital data centers to autonomous AI interfaces, your work will shape the fabric of the future. If you are passionate about solving complex problems at the intersection of AI, Cloud Computing, and Space Tech, we want to hear from you.
Responsibilities
- Architectural Leadership: Lead the end-to-end architectural design of scalable systems for the 'Project 2026' initiative, ensuring alignment with long-term strategic goals.
- Technical Strategy: Define technical roadmaps and best practices for distributed systems, microservices, and cloud-native environments.
- System Optimization: Oversee the migration of legacy infrastructure to next-gen platforms, focusing on performance, security, and cost-efficiency.
- Cross-Functional Collaboration: Work closely with product managers, designers, and engineers to translate business requirements into technical specifications.
- Innovation & Research: Stay ahead of industry trends, specifically in Generative AI and autonomous systems, to integrate cutting-edge solutions into our stack.
- Talent Development: Mentor a high-performing engineering team, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s degree in Computer Science, Information Systems, or a related field (or equivalent practical experience).
- Experience: 10+ years of experience in software architecture and full-stack development, with at least 3 years in a senior leadership role.
- Technical Skills: Deep expertise in distributed systems, cloud providers (AWS, GCP, or Azure), and containerization technologies (Kubernetes, Docker).
- Programming: Proficiency in high-level languages such as Python, Java, or Go.
- AI Integration: Demonstrated experience integrating AI/ML models into production environments.
- Soft Skills: Exceptional communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.