Jingcong Wang

I’m a Senior Software Engineer with 10 years building scalable, distributed systems and cloud-native infrastructure across GCP and Azure. I specialize in high-performance microservices, real-time data pipelines, and secure, event-driven architectures for mission-critical workloads.

At Google, I contributed to the architecture and development of the Fitbit Health Coach, integrating LLM-based conversational agents with real-time physiological data. I helped integrate Gemini LLMs into Fitbit’s wellness ecosystem and built cloud-native ML pipelines on TensorFlow, Vertex AI, and Kubeflow to automate data ingestion, training, and deployment.

I’ve delivered production-grade NLP/NLU frameworks using Transformers, BERT, and Gemini APIs for multi-turn dialog, intent classification, and sentiment analysis. I also implemented RLHF to refine LLM responses and created AI observability tools with React, TypeScript, and BigQuery, integrating Cloud Monitoring and Looker Studio for drift analytics and inference performance tracking.

Previously at Microsoft, I helped evolve Azure Machine Learning from a research prototype into a production-grade MLOps platform. I built core REST/gRPC services, designed secure backend workflows integrated with Azure Active Directory and Azure Resource Manager, and implemented event-driven messaging and automated CI/CD with Azure DevOps and GitHub Actions.