Job Description
We are pioneering the next generation of artificial intelligence infrastructure. As a 2026 Readiness AI Architect, you will be responsible for defining the technical roadmap that ensures our platforms are scalable, secure, and ahead of the curve for the technological landscape of 2026.
In this high-impact role, you will bridge the gap between theoretical AI advancements and practical engineering solutions. You will lead initiatives to future-proof our data pipelines, optimize deep learning models for edge computing, and integrate emerging quantum-ready protocols into our core stack. If you are a visionary engineer ready to shape the future of technology, we want to meet you.
Why Join Us?
- Work on cutting-edge AI infrastructure.
- Competitive compensation and equity package.
- Flexible remote-first culture.
Responsibilities
- Architect and oversee the end-to-end AI infrastructure roadmap designed for 2026 scalability and beyond.
- Design and implement resilient, high-throughput data pipelines capable of handling petabyte-scale unstructured data.
- Lead the integration of next-generation optimization techniques (e.g., Sparse Transformers, Quantization) into existing model architectures.
- Collaborate with quantum computing research teams to prepare our models for future hybrid computing environments.
- Establish best practices for MLOps, ensuring continuous integration and deployment of AI models with zero downtime.
- Conduct rigorous code reviews and architectural assessments to ensure system integrity and security compliance.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Minimum of 5 years of experience in designing scalable distributed systems and machine learning architectures.
- Deep expertise in Python, PyTorch, TensorFlow, and C++.
- Proven experience deploying large-scale models (LLMs, GNNs) in production environments.
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Kubernetes, Docker).
- Strong understanding of cybersecurity principles, particularly as they apply to AI model protection and adversarial attacks.