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Thomas Chen

@thomaschen

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Senior software engineer specializing in scalable cloud systems and LLM-powered products.

United States

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What I'm looking for

I seek roles building scalable, observable cloud-native systems and production AI/LLM features, with collaborative teams, strong engineering standards, and opportunities to mentor and shape technical roadmaps.

I am a senior software engineer with deep experience designing and operating large-scale, low-latency backend systems, AI/LLM integrations, and data pipelines across Azure, AWS, and GCP. I build production-grade microservices, event-driven architectures, and RAG/semantic search solutions that improve relevance, reduce latency, and increase system resilience.

I have led cross-functional teams at Microsoft, Amazon, and startups to productionize ML models, automate CI/CD and IaC, and deliver observability and performance improvements. My work includes driving architecture proposals, mentoring engineers, and achieving measurable impacts such as improved answer accuracy, reduced incident response times, and significant deployment and latency improvements.

Experience

Work history, roles, and key accomplishments

Current

Senior Software Engineer

Current

Microsoft

Jul 2024 - Present (1 year 8 months)

Design and build high-throughput, low-latency backend services for Bing's search platform and productionize LLM-powered features using Azure OpenAI and RAG, improving answer accuracy by over 35% and reducing latency through sidecar proxies by 20%.

C#.NET Core Azure OpenAI Go Kubernetes Kafka Apache Spark Terraform

Senior Software Engineer

Finny

Feb 2024 - Mar 2025 (1 year 1 month)

Built low-latency Python/FastAPI APIs and RAG pipelines with LangChain and Pinecone for an AI lead-generation platform, reducing processing latency by 50% and enabling scalable prospect identification for 40+ firms.

Python fastAPI Lang Chain Pinecone PostgreSQL Redis AWS Docker React

Senior Software Engineer

Amazon

Aug 2019 - Feb 2024 (4 years 6 months)

Designed and operated feature-rich, low-latency ML inference APIs and large-scale data pipelines using Java, Python, Spark, and AWS, improving throughput and enabling sub-100ms inference latencies for personalization systems.

Java Python AWS Apache Spark Kafka Go Kubernetes Terraform Redis

Software Engineer

Amazon

Mar 2016 - Aug 2019 (3 years 5 months)

Designed and maintained distributed Java microservices and SPA tools, refactoring monoliths into microservices and improving warehouse operational efficiency by 25% through internal React applications.

Java Spring Boot React AWS MySQL DynamoDB Docker Redis SQS

Education

Degrees, certifications, and relevant coursework

Rensselaer Polytechnic Institute

Bachelor of Science, Computer Science

2012 - 2015

Completed a Bachelor of Science in Computer Science with coursework and projects focused on software engineering, distributed systems, and data processing.