Job Description
Are you ready to architect the future?
Nexus Future Labs is seeking a visionary Lead Architect to spearhead our 2026 Horizon Initiative. As we prepare to redefine the boundaries of artificial general intelligence, we need a technical leader who can bridge the gap between theoretical research and scalable, production-grade engineering. This is not just a job; it is a mission to build the infrastructure that will power the next decade of technological evolution.
In this pivotal role, you will lead a world-class team of AI engineers, researchers, and data scientists. You will define the architectural standards for our proprietary LLMs and generative AI systems, ensuring they are secure, efficient, and scalable for enterprise deployment.
Responsibilities
- Architectural Leadership: Design and oversee the technical roadmap for the 2026 Horizon Initiative, ensuring alignment with long-term business goals.
- System Design: Develop robust, scalable system architectures for high-performance AI models and data pipelines.
- Team Mentorship: Mentor senior engineers and junior developers, fostering a culture of innovation and technical excellence.
- Technical Strategy: Evaluate emerging AI technologies (e.g., Transformer models, reinforcement learning) and integrate them into our core stack.
- Cross-Functional Collaboration: Work closely with product managers and data scientists to translate complex research into deployable features.
- Code Quality: Establish and enforce coding standards, best practices, and CI/CD pipelines to ensure software reliability.
Qualifications
- Education: Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
- Experience: 8+ years of experience in software engineering, with at least 5 years in a lead or architectural role within the AI/ML space.
- Technical Skills: Deep proficiency in Python, C++, and experience with major ML frameworks (PyTorch, TensorFlow, JAX).
- Modeling: Extensive experience designing and fine-tuning Large Language Models (LLMs) and Generative AI models.
- System Design: Strong background in distributed systems, cloud architecture (AWS/GCP/Azure), and microservices.
- Problem Solving: Proven ability to solve complex technical challenges and optimize system performance under pressure.