Job Description
Shape the Future of Intelligence. Nexus Horizon AI is at the forefront of the 2026 AI revolution. We are building the autonomous agent systems and next-generation Large Language Models that will redefine human-machine interaction. We are looking for a visionary 2026 AI Visionary Engineer to architect the core infrastructure of our flagship platform.
In this role, you won't just write code; you will define the technical roadmap for the AI landscape of tomorrow. You will lead a high-performing team of researchers and engineers in designing scalable, safe, and efficient AI agents capable of complex decision-making.
Responsibilities
- Architect and deploy scalable LLM inference pipelines optimized for 2026 performance standards and latency requirements.
- Design and implement multi-agent orchestration frameworks enabling autonomous task completion and complex reasoning.
- Lead the research and implementation of novel self-supervised learning techniques to improve model efficiency.
- Establish best practices for AI safety, alignment, and interpretability to ensure robust deployment in production environments.
- Collaborate with product teams to translate futuristic 2026 roadmaps into actionable technical specifications.
- Optimize cloud infrastructure (AWS/GCP) to handle petabyte-scale data processing for training and fine-tuning.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field (PhD preferred).
- 10+ years of experience in software engineering, with at least 5 years dedicated to Machine Learning and AI systems.
- Extensive expertise in building, training, and fine-tuning Large Language Models (GPT, LLaMA, Claude architectures).
- Strong proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- Proven experience with distributed training, MLOps, and high-performance computing clusters.
- Demonstrated success in leading cross-functional teams through complex technical challenges.
- Deep understanding of AI ethics, bias mitigation, and regulatory compliance standards.