Job Description
We are not just building software for today; we are architecting the infrastructure for the year 2026. As the Principal AI Architect, you will lead the charge in defining the next generation of predictive algorithms, autonomous systems, and ethical AI frameworks. Join our elite team in San Francisco and help shape the technological landscape of the future.
Why Join Us?
At Chronos Future Systems, we believe in a 2026-ready workforce. You will work with cutting-edge hardware, quantum-inspired computing models, and the most talented minds in the industry. We offer a competitive salary, equity packages, and a fully remote-first culture with hubs in San Francisco.
Role Overview
In this pivotal role, you will bridge the gap between theoretical AI research and practical, scalable engineering solutions. You will oversee the entire AI lifecycle, from data ingestion to model deployment, ensuring our systems are robust, secure, and ahead of the curve.
Responsibilities
- Define and execute the architectural vision for the 2026 product roadmap, integrating next-gen AI capabilities.
- Lead the design and implementation of scalable machine learning pipelines and deep learning architectures.
- Mentor a team of senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Evaluate and integrate emerging technologies (e.g., neuromorphic computing, edge AI) to maintain a competitive edge.
- Ensure data privacy, security, and ethical AI standards are met across all platforms.
- Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
- Conduct performance tuning and optimization of large-scale AI models in production environments.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years in a senior AI/ML architect role.
- Proven track record of leading complex AI initiatives from conception to deployment.
- Expert knowledge in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and containerization (Kubernetes/Docker).
- Experience with MLOps, data engineering, and model versioning tools.
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.
- Advanced degree in Computer Science, Artificial Intelligence, or a related field is preferred.