Job Description
Join Chronos AI Systems, the pioneer in predictive temporal intelligence, as we architect the foundational infrastructure for the year 2026. We are not just building software; we are engineering the future of human-machine symbiosis. If you are a visionary architect ready to redefine the boundaries of scalable AI systems, this is your opportunity to leave a lasting mark on history.
Why Join Us?
We are a remote-first, high-performance team dedicated to solving humanity's most complex temporal challenges. You will have the autonomy to design systems that process petabytes of data in real-time, optimizing for efficiency and foresight.
The Role:
As the Lead Systems Architect for the 2026 Initiative, you will oversee the end-to-end technical lifecycle of our flagship predictive engine. You will bridge the gap between theoretical machine learning models and production-grade distributed systems.
Responsibilities
- Design and implement high-availability, distributed microservices architecture capable of handling exabyte-scale data throughput.
- Lead the technical strategy for integrating cutting-edge neural networks with legacy infrastructure to ensure seamless operational continuity.
- Optimize system latency and throughput using advanced caching strategies and hardware acceleration (GPUs/TPUs).
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical blueprints.
- Mentor junior architects and engineers, fostering a culture of innovation and technical excellence.
- Conduct rigorous code reviews and architectural audits to ensure security and scalability standards are met.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- 10+ years of experience in software architecture, with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in designing scalable systems using Python, Java, or Go.
- Proficiency in containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, Google Cloud, or Azure).
- Strong understanding of distributed databases, message queues, and event-driven architectures.
- Experience implementing CI/CD pipelines and infrastructure-as-code (Terraform/Ansible).