Job Description
We are 2026 Systems, a pioneer in autonomous intelligence and next-generation predictive modeling. We are looking for a visionary Principal AI Architect to lead our engineering division. In this role, you won't just write code; you will architect the neural pathways that define the future of human-machine interaction.
If you are obsessed with scalability, possess a deep understanding of large language models, and want to build the technologies that will define the 2026 era, we want to meet you.
Why Join Us?
- Work on cutting-edge AI infrastructure.
- Competitive compensation package with equity options.
- Flexible remote-first culture with premium San Francisco amenities.
Responsibilities
- Lead Architectural Vision: Design and oversee the implementation of scalable, distributed AI systems capable of processing petabytes of real-time data.
- Model Development: Spearhead the research and deployment of advanced machine learning models, focusing on Natural Language Processing (NLP) and Computer Vision.
- Roadmap Strategy: Define the technical roadmap for 2026, identifying emerging technologies and integrating them into our core infrastructure.
- Team Mentorship: Cultivate a high-performance engineering culture, conducting code reviews, technical architecture reviews, and mentoring junior developers.
- System Optimization: Continuously optimize system latency, throughput, and cost-efficiency across cloud environments (AWS/GCP).
- Cross-Functional Collaboration: Partner with product managers, data scientists, and security experts to ensure AI solutions align with business goals.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, Robotics, or a related technical field (PhD preferred).
- Experience: 8+ years of professional software engineering experience, with at least 4 years in a senior or lead capacity within AI/ML.
- Technical Skills: Expert proficiency in Python, TensorFlow, PyTorch, or similar deep learning frameworks.
- Cloud Expertise: Strong experience designing systems on AWS, Google Cloud Platform, or Azure.
- System Design: Deep understanding of distributed systems, microservices architecture, and database management (SQL/NoSQL).
- Communication: Exceptional ability to translate complex technical concepts into actionable insights for non-technical stakeholders.