Job Description
We are building the technological foundation for the year 2026. At Nexus Future Systems, we are not just keeping up with the future; we are defining it. We are seeking a visionary Senior AI Architect to lead the design and implementation of next-generation generative models and scalable AI infrastructures.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and production-grade engineering. You will oversee the architecture of our core neural networks, ensuring they are robust, efficient, and ready for the massive scale of tomorrow's data.
If you are passionate about pushing the boundaries of what is possible with Artificial Intelligence and want to shape the digital landscape of the next decade, we want to meet you.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of complex AI systems, focusing on scalability, security, and performance optimization.
- Model Strategy: Define the roadmap for our machine learning models, selecting the right algorithms and frameworks to solve critical business problems.
- Code Review & Mentorship: Lead a team of brilliant engineers and data scientists, providing technical guidance and fostering a culture of excellence.
- System Integration: Integrate AI capabilities into our existing product ecosystem, ensuring seamless interoperability with legacy systems and new cloud-native applications.
- Innovation: Stay ahead of industry trends, particularly in Generative AI and Large Language Models, to propose innovative solutions for 2026 and beyond.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field (or equivalent extensive experience).
- Experience: 10+ years of experience in software engineering, with at least 5 years specifically in AI/ML architecture and deployment.
- Technical Skills: Deep proficiency in Python, C++, and ML frameworks such as TensorFlow, PyTorch, or JAX.
- Distributed Systems: Strong understanding of distributed computing, cloud infrastructure (AWS, GCP, or Azure), and containerization (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex technical challenges and delivering high-impact AI solutions.