Job Description
We are seeking a visionary Principal AI Architect to lead the development of next-generation intelligent systems for our 2026 roadmap. As we approach a new era of technological maturity, we are building the autonomous agency frameworks that will define the future of human-machine collaboration.
In this role, you will not just manage AI models; you will architect the entire infrastructure for Generative AI and Agentic Workflows. You will bridge the gap between theoretical research and production-grade deployment, ensuring our solutions are scalable, ethical, and transformative.
Why Join Us?
- Work on cutting-edge projects that define the 2026 AI landscape.
- Competitive salary and equity package.
- Flexible remote-first culture with premium San Francisco amenities.
- Access to the latest hardware and research labs.
Responsibilities
- Design and implement scalable neural architectures for large language models (LLMs) and multi-agent systems.
- Lead the end-to-end lifecycle of AI models, from research and prototyping to deployment and monitoring in production environments.
- Establish best practices for Responsible AI, ensuring fairness, transparency, and bias mitigation in all automated systems.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Optimize inference latency and reduce operational costs for high-volume AI workloads.
- Stay ahead of the curve by evaluating emerging technologies such as Quantum Computing integration and Neuromorphic chips.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Minimum of 8+ years of experience in software engineering and machine learning, with at least 4 years in a senior architect or principal engineering role.
- Extensive hands-on experience with Python, TensorFlow, PyTorch, and Hugging Face Transformers.
- Deep understanding of LLM fine-tuning, RAG (Retrieval-Augmented Generation), and prompt engineering.
- Strong expertise in cloud infrastructure (AWS, GCP, or Azure) and container orchestration (Kubernetes/Docker).
- Proven track record of deploying AI solutions that handle millions of requests per day.