• Designed and operated an AWS-native internal data platform transforming fragmented employee data into

clean, queryable datasets powering analytics, automation, and internal LLM/AI assistant workflows

• Developed MCP-integrated AI-assisted developer tooling to automate code reviews and push-to-production

checks, improving release velocity

• Built scalable APIs and services enabling self-service access to high-quality data for multiple

downstream teams and tools

• Owned systems end-to-end including architecture, deployment, observability, and on-call support

• Partnering with clients to architect and deploy full-stack, AI-driven solutions with containerized microservices and scalable generative AI frameworks, integrating large language models (LLMs) and cloud-native services.

• Supervising cloud migrations to AWS using serverless technologies such as Lambda and API Gateway, while implementing cost-optimized data pipelines and multi-region redundancies to reduce operational overhead.

• Leading development of a social music platform using React Native and Node.js/Express that integrates

gamification, real-time data processing, and AI-powered recommendations to enhance artist promotion.

• Architecting an event-driven infrastructure for core gamification features by leveraging AWS services

(EventBridge, SQS, SNS) to handle asynchronous workflows and decouple system components.

• Implementing streaming pipelines using Kafka for real-time ranking updates and recommendation processing, integrating SageMaker, TensorFlow, and other machine learning tools for data-driven insights.

• Designing and executing the database and systems architecture by leveraging DynamoDB for rapid

development, Redis for caching, and S3 for media storage to ensure robust performance and high availability.

• Developed a vendor-agnostic generative AI platform that supports diverse use cases—including interactive chat with source data, document generation, and content modification—by leveraging a Next.js/React frontend and a Python FastAPI backend.

• Engineered backend services that drive dynamic document processing and AI workflows, leveraging retrieval-augmented generation (RAG) techniques with embedding-based retrieval via Pinecone, agentic frameworks (Langchain/Langraph), and Amazon Bedrock for advanced natural language generation.

• Optimized cloud and container strategies by containerizing the platform with Docker and integrating AWS services (Lambda, S3, Fargate) to streamline deployments and maintain scalable, cost-effective operations across client environments.

• Facilitated the migration of a monolithic contact-center application to a service-oriented/microservices architecture on AWS, leveraging Docker containers with Elastic Kubernetes Service (EKS) to encapsulate and deploy Node.js microservices, resulting in consistent environments and a 90% reduction in deployment times.

• Developed individual front-end service components using JavaScript and React.js to establish a unified design system, creating the perception of a single application. Employed Fastify on the backend for efficient routing, request processing, and response generation.

• Leveraged AWS services such as EC2, Lambda, and Elastic Load Balancer (ELB) to automate infrastructure provisioning, deployment, and scaling of microservices, ensuring high availability and performance of the contact-center application while developing a standardized CI/CD pipeline.