Job Description
About 2026 Systems
We are building the infrastructure for the future. At 2026 Systems, we are not just predicting what comes next; we are engineering it. Our mission is to revolutionize the way humanity interacts with next-generation AI by delivering scalable, secure, and efficient solutions. We are looking for a visionary Principal AI Engineer to lead our core research and development team in San Francisco.
In this role, you will bridge the gap between theoretical AI research and production-grade software. You will be responsible for architecting systems that power our flagship platform, ensuring they are robust, scalable, and ready for the demands of the year 2026 and beyond.
Why Join Us?
- Impactful Work: Directly influence the roadmap of cutting-edge AI technology.
- Top-Tier Compensation: Competitive salary and equity package.
- Modern Environment: Work in a state-of-the-art office with hybrid flexibility.
Responsibilities
- Architect and design high-performance AI systems capable of processing petabytes of data in real-time.
- Lead the research and implementation of advanced machine learning algorithms, specifically in Generative AI and Large Language Models.
- Collaborate with cross-functional teams (Product, Design, Data Science) to translate complex business requirements into technical specifications.
- Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
- Optimize existing codebases for speed, scalability, and energy efficiency.
- Ensure all systems adhere to industry security standards and compliance regulations.
- Stay abreast of the latest advancements in the AI landscape to drive continuous innovation within the organization.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related field (or equivalent professional experience).
- Minimum of 7+ years of professional experience in software engineering and machine learning.
- Expert proficiency in Python, C++, and JavaScript/TypeScript.
- Deep understanding of deep learning frameworks such as PyTorch, TensorFlow, or JAX.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Strong problem-solving skills with a focus on distributed systems and high availability.
- Demonstrated leadership experience in managing engineering teams and projects.