Job Description
The Future is Now: Architecting Intelligence for 2026
Nexus Horizon Labs is at the forefront of the AI revolution, and we are looking for a visionary Senior Generative AI Architect to lead our upcoming projects. As we look toward 2026, our goal is to redefine human-computer interaction through advanced Large Language Models (LLMs) and autonomous agent systems.
In this role, you will not just write code; you will shape the ethical frameworks and technical architectures that will define the next generation of AI. If you are passionate about the future of technology and want to work with cutting-edge tools before they become standard, this is your opportunity.
Why Join Us?
- Work with a team of world-class researchers and engineers.
- Competitive equity package and top-tier healthcare.
- Remote-first culture with quarterly all-hands meetups in San Francisco.
Responsibilities
- Architect LLM Systems: Design and implement scalable, robust architectures for Generative AI applications, focusing on performance, safety, and accuracy.
- Prompt Engineering & Fine-Tuning: Lead the development of high-quality training data pipelines and fine-tune foundation models for specific industry verticals.
- Model Evaluation: Establish rigorous evaluation metrics and benchmarks to ensure model outputs meet safety and compliance standards.
- MLOps Integration: Oversee the deployment of models into production environments, ensuring high availability and low latency using Kubernetes and cloud infrastructure.
- RAG Strategy: Develop and optimize Retrieval-Augmented Generation strategies to enhance knowledge base accuracy.
- Cross-Functional Collaboration: Partner with product managers and designers to translate complex AI capabilities into user-friendly features.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in software engineering or machine learning, with at least 2 years specifically focused on Generative AI or NLP.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX; deep understanding of Transformer architectures and LLMs.
- Tools: Experience with MLOps tools (MLflow, Kubeflow), vector databases (Pinecone, Weaviate), and cloud platforms (AWS, GCP, or Azure).
- Creativity: Strong ability to think abstractly about problem-solving and adapt to rapidly evolving AI paradigms.
- Communication: Excellent written and verbal communication skills; able to explain complex technical concepts to non-technical stakeholders.