Rajiv Bharadwaja
Engineering Manager at Microsoft
Redmond, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolRajiv Bharadwaja is an Engineering Manager based in Redmond with a decade of experience building and scaling distributed systems, generative AI platforms, and production ML infrastructure across Microsoft and Google. He has led migrations to RAG-powered generative models, shipped Copilot Studio and Azure Bot Service features to GA, and now architects multi-agent GenAI workflows for security investigations in Microsoft Defender. His background spans low-latency social graph services, TPU tuning and orchestration for Vertex AI, and production Airflow automation for Google Cloud Datalab—evidence of deep systems and DevOps chops. Rajiv blends hands-on engineering (including scripting Airflow VM setups and TPU hyperparameter tuning) with people leadership, growing engineers into senior technical roles while maintaining 99.95%+ service availability. He’s comfortable bridging research and product: from algorithmic route planning and graph-based systems to prompt engineering, embeddings, and agentic workflows that operationalize LLMs at scale.
10 years of coding experience
23 years of employment as a software developer
Indian Institute of Technology MadrasUniversity of California, San Diego
Stackoverflow
100reputation
4kreached
4answers
0questions
Github Skills (16)
bash10
airflow10
gcp10
dockers9
docker9
python8
cicd7
scripting7
script7
sh7
infrastructure-as-code7
shell7
tensor2tensor6
google-cloud-ml6
wma6
Programming languages (3)
Github contributions (5)
googledatalab/notebooks
Nov 2017 - Aug 2018
Google Cloud Datalab samples and documentation
Role in this project:
DevOps Engineer
DevOps EngineerContributions:11 commits, 28 PRs, 55 pushes in 8 months
Contributions summary:Rajiv focused on automating and improving the setup and deployment processes for the Google Cloud Datalab notebooks repository, particularly the Airflow setup. They created and modified scripts to create Airflow VMs, install dependencies (like Apache Airflow and datalab), and configure the Airflow environment. The user also addressed issues in the startup scripts, and ensured the BigQuery pipeline samples integrated with the Composer environment.
gcpgooglenotebookgoogle-cloud-platformbigquery
rajivpb/hacking
May 2020 - May 2022
Contributions:1 push, 1 branch in 2 years
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