Principal AI Architect
United States · today
Lead the architecture, development, fine-tuning, and deployment of AI models and systems across OleOle's consumer SuperApp, including AskOle and real-time translation. Provide technical leadership to engineering teams while writing code and delivering production AI systems.
- Workplace
- Remote
- Seniority
- Principal
- Experience
- 10+ years
Skills
About the role
## Responsibilities • Lead the architecture, development, deployment, and ongoing evolution of AI initiatives across OleOle's global consumer SuperApp • Establish the overall AI architecture • Lead initiatives including AskOle, real-time multilingual translation, AI-powered sports history and content generation, the sports data engine, and future AI capabilities • Determine how models, technologies, and infrastructure should work together efficiently, reliably, and at global scale • Provide technical leadership alongside engineering teams and specialized AI engineers • Develop, fine-tune, optimize, integrate, and deploy AI models and systems • Build an adaptable, cost-efficient AI foundation without dependence on a single AI provider or technology • Make critical architectural decisions, write code, solve difficult engineering problems, and deliver functioning AI systems • Identify, evaluate, and implement emerging AI technologies for new products, capabilities, and business opportunities ## Requirements • 10+ years of software engineering, machine learning, or AI engineering experience • Demonstrated principal-level technical leadership • Extensive hands-on experience developing, training, fine-tuning, and deploying production AI models • Expert proficiency in Python, PyTorch, transformer architectures, and deep learning frameworks • Experience with open-source foundation models, including Llama, Qwen, Mistral, or equivalent • Strong experience with LoRA, QLoRA, supervised fine-tuning, model evaluation, and optimization • Deep knowledge of GPU computing, model quantization, batching, memory management, and inference performance • Production experience with vLLM, TensorRT-LLM, Triton Inference Server, or comparable inference technologies • Strong distributed-systems architecture and cloud infrastructure expertise • Ability to independently build and deploy complex AI systems • Experience leading engineering initiatives and establishing technical standards across multiple AI projects • Comfortable with deferred compensation and uncertain funding timelines • Willingness to travel • Understanding of football and international sports is a huge plus ## Benefits • Compensation accrued and payable following funding • After funding, transition to a regular/competitive salary • Equity ownership • OleX token participation/ownership in the OleOle group of companies
Posted Nov 9, 2026