Job Description
We are building the infrastructure for the future. As we approach the pivotal year of 2026, our mission is to pioneer systems that define the next era of human-machine collaboration. We are looking for a visionary Next-Gen AI Systems Architect to design scalable, ethical, and high-performance architectures for our flagship generative intelligence platforms.
In this role, you won't just maintain the status quo; you will architect the infrastructure required for autonomous decision-making and next-level generative AI at scale. You will bridge the gap between theoretical machine learning breakthroughs and production-ready, resilient systems.
Why join us?
- Work on cutting-edge projects that shape the trajectory of AI technology.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a presence in the heart of SF.
If you are ready to lead the charge into the AI revolution of 2026, we want to hear from you.
Responsibilities
- Design and implement resilient, distributed AI architectures capable of handling billions of requests.
- Lead the research, integration, and optimization of Large Language Models (LLMs) and multi-modal systems.
- Establish robust MLOps pipelines to ensure model reliability, retraining, and deployment efficiency.
- Define system governance frameworks to ensure AI safety, fairness, and ethical usage standards.
- Collaborate with cross-functional teams to translate high-level business requirements into technical roadmaps.
- Mentor senior engineers and foster a culture of technical excellence and innovation.
Qualifications
- 10+ years of experience in full-stack software engineering, with at least 5 years in AI/ML system architecture.
- Deep expertise in Python, TensorFlow, PyTorch, and modern AI frameworks.
- Strong proficiency in designing cloud-native applications on AWS, GCP, or Azure.
- Experience with vector databases, GPU orchestration (Kubernetes), and high-performance computing.
- Proven track record of leading high-performance engineering teams and driving technical strategy.
- PhD or Master’s degree in Computer Science, Machine Learning, or a related field is a plus.