Job Description
We are at the precipice of a technological revolution. As we look toward 2026, we are building the infrastructure that will define the next decade of human-machine interaction. Nexus Future Systems is seeking a visionary Senior AI Architect to lead our strategic roadmap and deploy cutting-edge generative models.
In this role, you won't just be writing code; you will be architecting the future. You will bridge the gap between theoretical AI research and scalable, production-ready enterprise solutions. If you are passionate about ethical AI, autonomous systems, and shaping the landscape of 2026, we want to hear from you.
Responsibilities
- Architect the 2026 Roadmap: Lead the technical strategy for our upcoming AI platform releases, ensuring scalability and innovation.
- Design Scalable Systems: Build robust, fault-tolerant AI architectures capable of processing massive datasets in real-time.
- Lead High-Performance Teams: Mentor and guide a team of data scientists and engineers, fostering a culture of excellence and continuous learning.
- Deploy Generative Models: Implement and optimize Large Language Models (LLMs) and multimodal AI systems for diverse business applications.
- Ensure Ethical AI: Establish governance frameworks to ensure AI outputs are fair, transparent, and bias-free.
- Cross-Functional Collaboration: Work closely with product managers, security experts, and stakeholders to translate complex requirements into technical blueprints.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field (PhD preferred).
- Experience: 8+ years of experience in software engineering and 5+ years specifically in AI/ML architecture.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with cloud platforms (AWS/GCP/Azure).
- Strategic Vision: Demonstrated ability to think long-term and define technical roadmaps for future years.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Deep expertise in solving complex optimization problems and system design challenges.