Jan 2024 – Apr 2025 · 1 yr 3 mos · India · Hybrid

• Developed and managed a robust, cloud-native Machine Learning Platform (MLP) leveraging Kubeflow Pipelines
• on Kubernetes to orchestrate large-scale distributed ML workflows
• − Engineered reusable custom components like Slack, Spark, Sagemaker, S3 in Python to standardized ML workflows.
• − Resolved critical inefficiencies in SageMaker training component that enhanced user efficiency and transparency,
• effectively addressing issues like unexpected pod deletions and ambiguous error logs, reduced unnecessary
• computational costs and increasing reliability by improving overall job management process.
• − Re-architected the ML Model Onboarding Flow which creates AWS infrastructure (ECR repos, S3 buckets, IAM roles,
• SageMaker permissions) and service accounts for that asset’s namespace for kubeflow to work, reduced model setup
• time from 15 minutes to just 4 seconds, boosting efficiency and productivity.
• − Migrated platform infrastructure from a proprietary system to AWS CDK (TypeScript), provisioning services such as S3,
• DynamoDB, RDS, IAM, VPCs, and Security Groups in a structured and scalable distributed system.
• − Migrated platform infrastructure from a proprietary system to a AWS CDK using Node.js (TypeScript), provisioning S3,
• DynamoDB, SageMaker, IAM, RDS, VPCs, and Security Groups in a structured and scalable distributed system.
• − Built a cloud-native automation and regression testing suite in Python with AWS Lambda to ensure continuous validation
• of pipeline correctness, reliability, and performance ahead of production deployment.
• − Advocated for backend engineering best practices and collaborated cross-functionally with product managers and
• designers to translate complex ML system needs into simple, scalable backend solutions.

May 2022 – Jan 2024 · 1 yr 8 mos · Bengaluru, Karnataka, India · Hybrid

• − Implemented core features and functionalities within the CRM (Central Platform across Khatabook) to boost user engagement and retention across multiple business verticals using Node Js ( TypeScript ).
• − Deployed and maintained Kubernetes clusters on AWS for CRM Platform, implemented CI/CD pipelines using Jenkins.
• − Designed a lead allocation engine that uses user roles and dynamic lead attributes to assign leads to suitable team
• members, improving conversion rates.
• − Engineered a Lead Type Executor module in Node.js to dynamically categorize and transition leads using configurable
• business rules, optimizing lead pipeline workflows.
• − Deployed Multiple Cron jobs using Kubernetes Cron Jobs and Python for automating follow-up tasks, assessing lead
• serviceability, and efficiently transitioning leads from the follow up queue to an active queue or paused queue to active
• queue.
• − Implemented dynamic UI configuration APIs with customizable components and granular access control.

Oct 2021 – May 2022 · 7 mos · Gurugram, Haryana, India

• − Conducted in-depth analysis of user interactions and behaviors on the Kaggle platform using Python Libraries such as Pandas and Tensorflow.
• − Designed and deployed an end-to-end pipeline for real-time analysis of user interactions using Kubernetes and Google Cloud Platform (GCP)

Oct 2020 – Oct 2021 · 1 yr · Noida, Uttar Pradesh, India

• − Designed and Developed robust and scalable backend services support the Klient platform’s (Klient is a Multi-tenant
• Group Insurance Brokerage Platform) core functionality using Python Django Framework.
• − Engineered a real-time ETL engine using Kafka and KsqlDB to optimize the platform’s primary search feature. Deployed
• the entire pipeline using Kubernetes on AWS, establishing an efficient event-driven queue infrastructure for an enhanced
• user experience.
• − Developed and deployed a suite of data models tailored for the extraction of valuable information from extensive
• insurance contracts, predominantly written in French, using Python libraries such as spaCy and FastApi Framework to
• facilitate the extraction process, enabling efficient data parsing and analysis.
• − Designed and Developed Multi-level text annotation tool backend to annotate lengthy insurance contracts using Python
• FastApi Framework.

Jan 2020 – Jun 2020 · 5 mos · Bhubaneshwar Area, India