Job Description
We are seeking a visionary Lead AI Systems Architect to define the technological roadmap for 2026 and beyond. Nexus Horizon AI is building the infrastructure that will power the next generation of generative intelligence. You will be responsible for designing scalable, secure, and efficient AI systems that push the boundaries of what is currently possible.
In this role, you will bridge the gap between theoretical research and production engineering, ensuring our models are not only state-of-the-art but also commercially viable and ethically sound. Join a team of world-class engineers and researchers dedicated to shaping the future of artificial intelligence.
Responsibilities
- Architect Next-Gen AI Infrastructure: Design and deploy scalable distributed systems for training and serving large language models (LLMs) and multi-modal AI agents.
- Optimize Model Performance: Implement cutting-edge techniques in model compression, quantization, and inference optimization to reduce latency and costs.
- Lead Technical Strategy: Define the technical vision for our AI stack, evaluating emerging technologies (e.g., quantum-resistant cryptography, neuromorphic computing) for future readiness.
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and security experts to integrate AI capabilities into consumer-facing products.
- Ensure Ethical AI Compliance: Establish guardrails and monitoring systems to ensure AI outputs are safe, unbiased, and aligned with regulatory standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 8+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning infrastructure and large-scale distributed systems.
- Technical Stack: Deep expertise in Python, C++, and frameworks such as PyTorch, TensorFlow, or JAX. Experience with Kubernetes and cloud platforms (AWS/GCP/Azure).
- System Design: Proven track record of designing high-availability, fault-tolerant systems capable of handling petabyte-scale data.
- Future-Forward Mindset: Demonstrated ability to anticipate industry trends and adapt architectures to meet future demands (e.g., AGI readiness).