Job Description
Welcome to the vanguard of technological evolution. Nexus Future Labs is pioneering the infrastructure for the year 2026 and beyond. We are seeking a visionary Senior AI Architect to lead the design of next-generation autonomous systems and generative AI frameworks. This is not just a job; it is an opportunity to define the ethical and technical landscape of the future.
In this high-impact role, you will bridge the gap between theoretical AI research and scalable production environments. You will work with a world-class team of quantum physicists, cognitive scientists, and software engineers to build the digital nervous system of the 21st century.
Why join us?
- Shape the roadmap for AGI (Artificial General Intelligence) adoption.
- Competitive compensation package with equity options.
- Work in a state-of-the-art innovation hub.
If you are driven by the challenge of building systems that think, adapt, and evolve, we want to hear from you.
Responsibilities
- Lead the architectural design of large-scale AI models, focusing on efficiency, safety, and scalability for deployment in 2026.
- Define and implement the technical roadmap for integrating quantum computing principles into classical machine learning pipelines.
- Mentor senior engineers and data scientists, fostering a culture of innovation and rigorous technical excellence.
- Collaborate with product teams to translate complex AI capabilities into user-centric features.
- Establish ethical guidelines and safety protocols for autonomous decision-making systems.
- Optimize neural network architectures to reduce latency and improve inference speed in edge computing environments.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering with a strong focus on AI/ML systems.
- Deep expertise in Deep Learning frameworks (TensorFlow, PyTorch, JAX) and large language model (LLM) architecture.
- Proven track record of leading cross-functional teams in the development of production-grade AI systems.
- Strong understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Excellent communication skills with the ability to articulate complex technical concepts to diverse stakeholders.