Job Description
We are at the forefront of the Artificial Intelligence revolution. As we accelerate towards the defining era of 2026, Nexus Horizon is seeking a visionary Lead AI Architect to build the infrastructure for the next generation of autonomous systems. You will be responsible for designing scalable, secure, and high-performance generative AI solutions that redefine human-machine interaction.
In this pivotal role, you won't just write code; you will architect the future. You will work with world-class engineers and researchers to deploy state-of-the-art Large Language Models (LLMs) and multimodal agents that power enterprise-grade applications globally.
Why join Nexus Horizon?
- Future-Proofing: Work on cutting-edge technology designed to lead the market into 2026 and beyond.
- Innovation: A culture that prioritizes experimental research and rapid deployment.
- Impact: Your work will directly influence how millions of users interact with intelligent systems.
Responsibilities
- Architect Scalable AI Infrastructures: Design and implement robust distributed systems for training and deploying large-scale Generative AI models.
- Model Lifecycle Management: Oversee the entire ML lifecycle, from data ingestion and preprocessing to model fine-tuning, evaluation, and production deployment.
- Performance Optimization: Engineer high-throughput inference pipelines and optimize model latency to ensure real-time responsiveness in critical applications.
- Multi-Modal Integration: Spearhead the integration of text, vision, and audio data streams into unified AI agents.
- AI Safety & Alignment: Implement safety protocols and alignment techniques to ensure AI outputs are reliable, unbiased, and compliant with ethical standards.
- Team Leadership: Mentor a team of ML engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: Minimum of 5+ years of experience in software engineering, with at least 3 years specifically focused on Machine Learning and Deep Learning systems.
- Technical Stack: Deep expertise in Python, PyTorch, or TensorFlow; experience with distributed computing frameworks (Ray, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
- Generative AI: Proven track record of working with LLMs (e.g., GPT, LLaMA, Claude), RAG architectures, and fine-tuning methodologies.
- System Design: Strong understanding of system design patterns, microservices, and high-availability architecture.
- Problem Solving: Ability to tackle complex, ambiguous problems and deliver innovative solutions in a fast-paced environment.