Forward Deployed Engineer for Sora Union

Role overview

Build and deploy AI solutions that address real operational needs, working directly with customers as well as engineering, product design, and quality teams. This forward deployed engineering role spans the full project lifecycle: clarifying requirements, prototyping, integrating data, deploying models, and improving performance in live customer environments. It calls for an entrepreneurial approach to ambiguous problems and a focus on delivering useful, production-ready systems.

Responsibilities - Serve as a technical partner to customers and translate their operational needs into AI-powered applications. - Own implementations from data preparation and prototyping through deployment, monitoring, and debugging. - Improve latency and throughput using techniques such as model compression, quantization, and efficient serving. - Build prompt workflows, context management, and retrieval-augmented generation approaches to improve model accuracy. - Work across engineering, product design, and QA to deliver solutions in customer environments.

Requirements - At least three years of experience building and deploying production AI or machine learning models. - Strong Python skills and experience with deep learning frameworks such as TensorFlow or PyTorch. - Experience with LLM orchestration tools, such as LangChain or LlamaIndex, and MLOps platforms such as MLflow, Kubeflow, or Weights & Biases. - Ability to build low-latency REST APIs and work with SQL or NoSQL databases for data integration. - Experience working directly with stakeholders to define requirements and deliver solutions. - Experience containerizing models with Docker and deploying to a cloud platform such as AWS, GCP, or Azure; able to take initiative in fast-moving, ambiguous settings.