Job Description
Shape the Future of Intelligence
Nexus Horizons is at the forefront of the next technological revolution. We are seeking a visionary Senior Generative AI Architect to lead the development of next-generation Large Language Models (LLMs) and generative systems designed for the 2026 landscape. If you are passionate about pushing the boundaries of AI, ethical AI, and scalable infrastructure, we want to meet you.
In this role, you will define the architectural blueprint for our AI ecosystem, ensuring our solutions are not only cutting-edge but also robust, secure, and scalable.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable, high-performance generative AI pipelines and MLOps infrastructure tailored for future-scale deployment.
- Model Optimization: Lead the fine-tuning and optimization of proprietary and open-source models (e.g., GPT, Llama, Claude) to enhance accuracy, reduce latency, and minimize hallucinations.
- RAG & Vector Systems: Spearhead the development of Retrieval-Augmented Generation (RAG) architectures and vector database strategies to ensure context-aware AI interactions.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineering teams to translate complex business requirements into technical AI solutions.
- Ethical AI Compliance: Establish guidelines and best practices for AI safety, bias mitigation, and responsible data usage in compliance with evolving regulations.
- Performance Engineering: Conduct rigorous testing, benchmarking, and cost optimization to ensure models run efficiently on cloud-native environments.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically focused on Machine Learning and Deep Learning systems.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of transformer architectures and NLP.
- Infrastructure: Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Generative AI: Proven track record of working with LLMs, prompt engineering, and deploying generative models into production environments.
- Problem Solving: Strong ability to debug complex distributed systems and optimize performance under heavy load.