Job Description
We are at the precipice of the next technological evolution, and Nexus Dynamics is looking for a visionary Lead AI Architect to define the infrastructure for the 2026 Horizon. In this pivotal role, you will not just build models; you will architect the ethical and technical framework for Artificial General Intelligence (AGI) as we approach the 2026 target date.
If you are passionate about the future of machine learning, possess a deep understanding of neural architectures, and want to lead a team that will redefine human-machine interaction, we want to meet you. This is an opportunity to leave a lasting legacy in the tech landscape.
Responsibilities
- Architect the 2026 Roadmap: Define the technical vision and architectural standards for the next phase of our AI evolution, ensuring scalability and ethical compliance by 2026.
- Lead High-Stakes Projects: Spearhead the development of proprietary Large Language Models (LLMs) and multi-agent systems designed to solve complex real-world problems.
- Technical Mentorship: Guide a team of senior engineers and data scientists, fostering a culture of innovation, continuous learning, and rigorous research.
- Bridge Research and Production: Translate cutting-edge academic research into deployable, production-grade software solutions.
- Stakeholder Collaboration: Work closely with product managers, legal teams, and executives to align AI capabilities with business objectives and regulatory standards.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 10+ years of experience in software engineering and AI development, with at least 5 years in a leadership or architect role.
- Technical Expertise: Deep proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing systems (Kubernetes, AWS/Azure/GCP).
- Domain Knowledge: Proven track record of working on NLP, Computer Vision, or Reinforcement Learning projects.
- Strategic Mindset: Ability to think long-term and navigate ambiguity while driving project execution.