Job Description
Join Nexus 2026, the premier think tank and engineering firm dedicated to defining the technological landscape of the next decade. We are not just building software; we are architecting the future. As a Senior AI Architect, you will lead the charge in developing next-generation generative models, ethical AI frameworks, and quantum-ready neural networks designed to solve humanity's most complex challenges by 2026.
You will operate at the intersection of theoretical computer science and practical engineering, collaborating with world-class researchers to deploy scalable solutions that redefine what is possible in artificial intelligence. If you are passionate about the singularity, ethical AI, and building systems that stand the test of time, this is your stage.
Why Nexus 2026?
- Future-Proofing: Work on technologies that will define the market in 2026 and beyond.
- Impact: Your code will directly influence global policy and technological infrastructure.
- Equity: Competitive equity package tied to long-term company success.
Responsibilities
- Design and architect scalable, high-performance AI infrastructure capable of handling petabyte-scale data streams.
- Lead the research and implementation of cutting-edge Large Language Models (LLMs) and reinforcement learning algorithms.
- Define the technical roadmap for Nexus 2026, ensuring alignment with long-term strategic goals.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Ensure all AI systems adhere to strict ethical guidelines, bias mitigation protocols, and safety standards.
- Collaborate with cross-functional teams including product management, legal, and security to integrate AI solutions into core products.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years focused specifically on Machine Learning and Artificial Intelligence.
- Deep expertise in Python, C++, and TensorFlow or PyTorch.
- Proven track record of deploying large-scale AI systems in production environments.
- Master’s or PhD degree in Computer Science, Mathematics, or a related field is highly preferred.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and microservices.
- Experience with quantum computing concepts and their application to classical ML problems is a plus.