Job Description
Are you ready to architect the digital infrastructure of tomorrow?
Nexus Horizon Systems is at the forefront of the 2026 technological revolution, building the autonomous agents and generative intelligence platforms that will redefine human-computer interaction. We are seeking a visionary Senior AI Architect to lead our research and engineering division.
In this role, you won't just implement existing models; you will push the boundaries of what is possible, designing scalable neural architectures that power our next-generation enterprise solutions. If you are passionate about the convergence of quantum computing and artificial intelligence, and you want to leave a legacy in the tech landscape of 2026, we want to meet you.
Why Join Us?
- Work on next-gen AI agents and LLM fine-tuning frameworks.
- Competitive equity and benefits package.
- Opportunity to shape the 2026 AI roadmap from the ground up.
Responsibilities
- Lead the end-to-end design and implementation of proprietary machine learning models focused on predictive analytics and autonomous decision-making.
- Architect high-throughput, low-latency inference pipelines capable of handling petabytes of real-time data streams.
- Collaborate with cross-functional teams (Data Science, Product, Security) to integrate AI capabilities into consumer and enterprise products.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Research and prototype novel algorithms that align with our vision for the 2026 technological horizon.
- Ensure model robustness, fairness, and ethical AI compliance across all deployed systems.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in software engineering with a strong focus on Machine Learning and Deep Learning.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of Large Language Models (LLMs), Transformers, and Retrieval-Augmented Generation (RAG).
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying scalable AI models to production environments.
- Strong communication skills with the ability to translate complex technical concepts for diverse stakeholders.