Job Description
Are you ready to build the infrastructure of tomorrow?
Nexus Horizon Corp is on a mission to pioneer the technological landscape of 2026. We are seeking a visionary AI Systems Architect to lead the design and implementation of next-generation artificial intelligence solutions. You won't just be maintaining systems; you will be architecting the future of human-machine interaction.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable production systems. You will work with a world-class team of engineers and data scientists to deploy models that are not only powerful but also ethical, efficient, and ready for the demands of the next decade.
Why Join Us?
- Work on cutting-edge projects that define the industry standard for 2026.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to state-of-the-art hardware and research facilities.
Responsibilities
- Design and architect scalable, high-performance AI infrastructure capable of processing petabytes of data.
- Lead the end-to-end deployment of Large Language Models (LLMs) and generative AI agents into production environments.
- Collaborate with cross-functional teams to define technical roadmaps that align with our 2026 strategic vision.
- Implement robust monitoring, logging, and alerting systems to ensure system reliability and uptime.
- Establish best practices for model governance, data privacy, and ethical AI usage.
- Optimize model inference speed and resource utilization to reduce operational costs.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related technical field.
- 7+ years of experience in software engineering, with at least 3 years specifically in AI/ML infrastructure.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of distributed systems, microservices architecture, and containerization (Kubernetes, Docker).
- Experience with cloud platforms (AWS, GCP, or Azure) and serverless architectures.
- Strong grasp of MLOps principles, CI/CD pipelines, and data versioning tools.