Senior Full Stack Engineer
Carson Rodrigues
Building scalable, cloud-native, AI-powered systems with NestJS, TypeScript, AWS.
Scalable BackendAPI DesignCloud & DevOpsLLM IntegrationMicroservices
Let's Build Something Amazing Together
Whether you need to scale ops, ship fast, or unlock new product capabilities with AI — let's bring it to life with clarity and speed.
5+
Production Systems
40K+
Users Served
4+
Years Experience
99.9%
Uptime
Experience
Senior Full Stack Engineer
Odasie, Thailand • Remote
Jan 2025 – Present
- •Led end-to-end delivery of 5+ production SaaS and AI systems
- •Designed cloud-native architectures on AWS, reducing deployment failures by 70%
- •Built LLM-powered automation systems, reducing manual processing by ~50%
AWS
NestJS
LLMs
TypeScript
Docker
Terraform
Senior Software Engineer
VoiceQube Inc., USA • Remote / Contract
Sep 2023 – Present
- •Architected and scaled NestJS + AWS backend serving 40,000+ golf courses
- •Designed low-latency distributed systems, improving throughput by ~2×
- •Built geospatial indexing and real-time GPS computation pipelines
NestJS
AWS
MongoDB
Redis
WebSockets
Terraform
Tech Stack
Tools & technologies I use daily
TypeScript
NestJS
React
AWS
MongoDB
LLMs
Docker
Git
Featured Projects
Distributed microservices platform for AI-driven interview simulation, resume analysis, and job preparation. Built with real-time AI interview system using WebRTC, LiveKit, and Pipecat.
Key Features:
- •Real-time AI interview system with low-latency audio/video streaming
- •LLM routing and orchestration via OpenRouter with GPT-4, Claude, and Gemini
- •Session-aware interview state management
- •Async processing pipelines using AWS SQS FIFO queues
- •99.9% uptime under concurrent workloads
WebRTC
LiveKit
Pipecat
ElevenLabs
Deepgram
OpenRouter
AWS SQS
LLMs
RealStream ChatDoc Platform
Real-time document intelligence platform combining streaming ingestion and AI-powered querying. Built with Kafka-based ingestion pipeline and vector-based document chat.
Key Features:
- •Kafka-based ingestion pipeline on AWS for near-real-time analytics
- •AWS Glue and Athena for ETL workflows and schema management
- •Vector-based document chat using Pinecone, Algolia, and OpenAI
- •Streaming ingestion for document processing
Kafka
AWS Glue
AWS Athena
Pinecone
Algolia
OpenAI
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