Job Description
We are seeking a visionary 2026 AI Systems Architect to lead the development of next-generation artificial intelligence infrastructures. At Nexus Horizon, we are not just predicting the future; we are building it. In this pivotal role, you will design and implement scalable AI solutions that integrate quantum-ready architectures with cutting-edge deep learning models. You will work at the intersection of hardware and software, ensuring our systems are robust, ethical, and ready for the demands of the post-silicon era. If you are passionate about shaping the technological landscape of the future, we want to hear from you.
Why Join Nexus Horizon?
- Impactful Work: Directly influence the trajectory of global AI development.
- Future-Ready: Work with bleeding-edge technologies including Neuromorphic Computing and Edge AI.
- Competitive Compensation: Comprehensive benefits package including stock options and remote flexibility.
Responsibilities
- Architect Design: Design and oversee the deployment of large-scale AI infrastructure capable of processing petabyte-scale data streams in real-time.
- Quantum Integration: Bridge the gap between classical AI models and future quantum computing paradigms to optimize algorithmic performance.
- System Optimization: Enhance the efficiency and accuracy of machine learning pipelines, focusing on latency reduction and energy consumption.
- Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Ethical AI Governance: Establish frameworks for responsible AI development, ensuring compliance with evolving global regulations.
- Prototyping: Rapidly prototype and validate new AI concepts and architectural patterns before full-scale implementation.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: Minimum of 8+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and distributed systems.
- Domain Knowledge: Deep understanding of Large Language Models (LLMs), Neural Networks, and Reinforcement Learning.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems in high-pressure environments.
- Communication: Exceptional verbal and written communication skills for translating technical concepts to non-technical stakeholders.