Job Description
We are on the cutting edge of innovation, defining the technological landscape for the year 2026 and beyond. Nexus Future Systems is seeking a visionary Senior AI Architect to lead our research and development division. In this pivotal role, you will be responsible for architecting the next generation of artificial intelligence systems that will power our enterprise solutions.
As we prepare for the rapid evolution of AI in 2026, we need a leader who can bridge the gap between theoretical research and scalable production environments. You will work with a world-class team to define standards, mentor junior engineers, and ensure our infrastructure is ready for the future of computing.
Why Join Us?
We offer a competitive benefits package, remote-first flexibility, and the opportunity to shape the future of technology. If you are passionate about building AI systems that are not just smart, but ethical, scalable, and transformative, we want to hear from you.
Responsibilities
- Lead the architectural design and implementation of large-scale AI and Machine Learning systems for the 2026 roadmap.
- Define technical standards and best practices for AI model deployment, focusing on scalability and performance.
- Conduct deep research into emerging AI technologies, including Generative AI, LLMs, and Reinforcement Learning.
- Collaborate with cross-functional teams (Data Science, Engineering, Product) to integrate AI solutions into core products.
- Mentor and guide a team of data scientists and engineers, fostering a culture of innovation and continuous learning.
- Evaluate and select the latest hardware accelerators and cloud infrastructure to optimize AI inference.
- Ensure all AI systems adhere to strict ethical guidelines, data privacy regulations, and bias mitigation protocols.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Minimum of 8+ years of experience in software engineering and AI/ML architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of designing and deploying production-grade Machine Learning models at scale.
- Strong understanding of distributed systems, cloud architectures (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Experience with MLOps pipelines, model monitoring, and A/B testing frameworks.
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.