Job Description
We are seeking a visionary Senior AI Architect to lead the technical blueprint for our 2026 Global Neural Grid initiative. At Nexus Horizon Labs, we are not just building software; we are engineering the cognitive foundation of the next industrial revolution. This is a rare opportunity to shape the trajectory of artificial general intelligence in a high-impact environment.
In this pivotal role, you will define the architectural pillars that will support our enterprise-level AI solutions, ensuring scalability, security, and ethical integrity. You will bridge the gap between theoretical research and production-grade systems, working alongside a world-class team of quantum engineers and data scientists.
Why Join Us?
- Future-Ready Role: Directly influence the technical roadmap leading up to 2026.
- Premium Compensation: Competitive salary and equity package.
- State-of-the-Art Environment: Work with cutting-edge GPU clusters and quantum computing prototypes.
Responsibilities
- Architect and design scalable, fault-tolerant machine learning infrastructure for the 2026 release cycle.
- Lead the migration to decentralized AI models and edge computing architectures.
- Define best practices for data governance, model transparency, and ethical AI deployment.
- Collaborate with cross-functional product teams to translate business requirements into technical roadmaps.
- Oversee the deployment of Large Language Models (LLMs) and generative AI tools across enterprise clients.
- Conduct rigorous performance tuning and cost optimization for large-scale inference pipelines.
- Mentor junior architects and engineers, fostering a culture of continuous innovation.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 8+ years of experience in full-stack software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of designing high-availability systems handling petabytes of data.
- Strong understanding of cloud ecosystems (AWS, GCP, or Azure) and containerization (Kubernetes/Docker).
- Experience with MLOps, CI/CD pipelines, and model versioning strategies.
- Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.