• 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Engineered and deployed a massive-scale multi-agent browser automation system on AWS. Architected workflow orchestration to handle complex document processing and form submissions autonomously, driving a 10x capacity improvement.

• 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 & 𝗔𝗪𝗦 𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻: This architecture was selected and showcased by Amazon's SVP of AGI (Rohit Prasad) at the AWS Summit as the defining enterprise case study for Amazon Nova Act.

• 𝗦𝘁𝗮𝗰𝗸: Python, AWS (AGI Labs, Lambda, Step Functions, Bedrock), Amazon Nova Act, LangChain.

• 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗠𝗟𝗢𝗽𝘀 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 ($𝟱𝟬𝟬𝗕+ 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼): Architected and deployed an end-to-end MLOps platform supporting 300+ data scientists and powering real-time risk analytics for a $500B+ lending portfolio.

• 𝗦𝗰𝗮𝗹𝗲 & 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Built reproducible infrastructure (Sagemaker, ECS, Terraform) with automated CI/CD and model governance, achieving a 40% faster model deployment rate.

• 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀: Developed a multi-agent solution to automate code refactoring workflows, yielding a 70% improvement in developer productivity.

• 𝗦𝘁𝗮𝗰𝗸: Python, Terraform, AWS (SageMaker, S3, ECS, Bedrock), MLflow, Jenkins

MLOps, Distributed Computing, Production ML Systems

• 𝗠𝗟 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀: Re-architected core analysis pipelines to serve decentralized, multi-institution environments across 60+ sites, driving a 300% increase in platform adoption.

• 𝗛𝗶𝗴𝗵-𝗣𝗿𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻: Engineered custom machine learning models for complex, high-resolution image segmentation, improving model accuracy by 30% in highly constrained data environments.

• 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 (𝗤𝗖): Architected and deployed an automated QC platform that eliminated manual processing bottlenecks, accelerating expert review workflows by 30%.