Job Description
We are pioneering the 2026 Vision Initiative, a revolutionary program designed to redefine the boundaries of generative intelligence and next-generation compute infrastructure. We are seeking a world-class Principal AI Architect to lead our core engineering team in architecting systems that will define the future of enterprise AI.
In this high-impact role, you will bridge the gap between theoretical research and production-grade deployment. You will not just write code; you will define the architectural paradigms for the technologies that will power the 2026 global economy. If you are a visionary engineer who thrives in ambiguity and demands excellence, we want to hear from you.
Responsibilities
- Architect and deploy scalable, high-performance AI infrastructure capable of processing petabyte-scale datasets in real-time.
- Lead the Research & Development strategy for the 2026 roadmap, identifying emerging technologies in LLMs and Quantum AI.
- Mentor and cultivate a high-performing engineering team, fostering a culture of innovation and technical excellence.
- Define and enforce architectural standards, ensuring system reliability, security, and scalability.
- Collaborate with cross-functional product leaders to translate complex business requirements into robust technical solutions.
- Drive the implementation of MLOps pipelines to automate model training, validation, and deployment cycles.
- Conduct deep-dive technical reviews and code audits to ensure adherence to best practices.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Minimum of 10+ years of experience in software architecture, with at least 5 years specifically in AI/ML engineering.
- Deep expertise in Python, TensorFlow, PyTorch, and distributed computing frameworks (Kubernetes, Docker, AWS/GCP/Azure).
- Proven track record of designing and shipping large-scale machine learning systems from the ground up.
- Strong understanding of natural language processing (NLP) and generative model architectures.
- Exceptional leadership skills with a history of mentoring senior engineers and influencing technical roadmaps.
- Experience with privacy-preserving technologies (e.g., Federated Learning, Differential Privacy).