Alexandre Jacquemot is a Senior Software Engineer with 11 years of experience building high-throughput, reliable coordination and logging systems across Datadog’s intake, storage, and orchestration stacks. Based in New York after a long tenure in Paris, he specializes in backend infrastructure, observability, and performance optimization—skills evidenced by contributions to widely used open-source Datadog projects that improved batching, retry logic, and network performance for serverless log pipelines. He moves confidently between hands-on coding, testing core components, and DevOps-oriented improvements, making systems more resilient and efficient. A curious and proactive problem-solver, Alexandre has repeatedly taken on cross-cutting challenges from logs intake to shard orchestration. His engineering approach blends academic grounding in microelectronics and computer security with practical experience at scale, and he often surfaces subtle reliability wins that aren’t obvious from feature lists alone.
11 years of coding experience
8 years of employment as a software developer
Master’s Degree Microelectronics Computer Science and New Technologies , Master’s Degree Microelectronics Computer Science and New Technologies at École des Mines de Saint-Étienne
Preparation for national competitive entrance exams to leading French Grandes Ecoles Mathematics Physics and Engineering Science , Preparation for national competitive entrance exams to leading French Grandes Ecoles Mathematics Physics and Engineering Science at Lycée Louis Pasteur
Exchange Program Computer Security & Smart Objects, Exchange Program Computer Security & Smart Objects at EURECOM
Contributions:190 commits, 336 PRs, 1149 pushes in 2 years 3 months
Contributions summary:Alexandre primarily worked on modifying and merging code related to the logs-agent within the Datadog Agent repository. Their contributions included changing log severity levels, reverting changes, and merging a logs-agent code base, which indicates a focus on the backend infrastructure for log collection and processing. The user also interacted with the code in `pkg/collector/corechecks/embed/logs-agent.go` and `pkg/logs/decoder/decoder_test.go`, showcasing the ability to modify and test core components related to log processing.
Repo of AWS Lambda and Azure Functions functions that process streams and send data to Datadog
Role in this project:
Back-end Developer & DevOps Engineer
Contributions:47 commits, 6 PRs, 74 pushes in 4 months
Contributions summary:Alexandre primarily focused on improving the Datadog serverless function's ability to process logs and send data. Their work involved refactoring the code to utilize an HTTP client for sending batches of logs, improving the retry logic, and optimizing network performance by using sessions. They also made various improvements and refactoring to metadata, TCP client, and batching, indicating a focus on performance and reliability.
azure-functionsserverlessaws-lambdastreamsaws
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Alexandre Jacquemot - Senior Software Engineer - Coordination Systems