Job Description
Join the Architects of Tomorrow.
Quantum Horizon Systems is pioneering the next generation of cognitive computing. We are seeking a visionary AI Lead Architect to design the robust, scalable, and ethical infrastructure for our 2026 roadmap. You will not just write code; you will define the architectural standards for the future of human-machine interaction.
In this role, you will bridge the gap between theoretical AI research and production-grade deployment, leading a world-class team of data scientists and engineers.
Responsibilities
- Design and implement end-to-end scalable AI architectures for next-gen Large Language Models (LLMs) and generative AI agents.
- Lead architectural decisions regarding data pipelines, model training, and inference optimization for high-traffic environments.
- Establish best practices for MLOps, ensuring model reproducibility, monitoring, and continuous integration/deployment.
- Mentor and guide a team of junior and senior engineers, fostering a culture of innovation and technical excellence.
- Collaborate with cross-functional product teams to translate complex business requirements into technical AI solutions.
- Ensure AI systems adhere to strict ethical guidelines, data privacy standards, and regulatory compliance (GDPR, CCPA).
- Stay ahead of the curve in emerging AI technologies, evaluating their applicability to our strategic roadmap.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in software engineering, with at least 5 years in leading AI/ML infrastructure projects.
- Expert proficiency in Python, PyTorch, and TensorFlow frameworks.
- Deep understanding of Deep Learning, Natural Language Processing (NLP), and Computer Vision algorithms.
- Proven experience designing distributed systems and cloud-native architectures (AWS, GCP, or Azure).
- Strong background in MLOps tools and methodologies (Kubeflow, MLflow, Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.