Job Description
We are seeking a visionary Lead Systems Architect to spearhead the 2026 Strategic Initiative, a project designed to revolutionize our core infrastructure and pioneer next-generation AI integration. At Horizon Technologies, we don't just predict the future; we build it. You will be at the helm of architectural decisions that will define our product roadmap for the coming decade, ensuring our systems are scalable, resilient, and future-proof. If you are passionate about pushing the boundaries of technology and leading high-performance teams, we want to hear from you.
Responsibilities
- Architect the Future: Design and oversee the implementation of complex, scalable system architectures for the 2026 initiative, focusing on AI-driven automation and cloud-native scalability.
- Strategic Leadership: Define technical roadmaps and standards that align with long-term business goals, guiding the engineering team through emerging technological trends.
- Team Mentorship: Cultivate a high-performance engineering culture by mentoring senior engineers and fostering professional growth within the department.
- Performance Optimization: Monitor system performance, identify bottlenecks, and drive continuous improvements to ensure 99.99% uptime and minimal latency.
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and security experts to ensure technical feasibility and business alignment.
- Security & Compliance: Implement robust security protocols and ensure all architectural decisions adhere to strict data protection regulations.
Qualifications
- Experience: 8+ years of experience in systems architecture, with at least 3 years in a lead or architectural role.
- Technical Stack: Deep expertise in distributed systems, microservices, and containerization (Kubernetes, Docker).
- Programming: Proficiency in Python, Go, or Java, with a strong understanding of asynchronous programming and event-driven architectures.
- Cloud Mastery: Extensive experience with major cloud providers (AWS, GCP, or Azure) and serverless technologies.
- AI/ML Integration: Solid understanding of integrating machine learning models into production environments.
- Problem Solving: Demonstrated ability to solve complex technical challenges and make critical architectural decisions under pressure.