Rohit is available for hire
Hire RohitRohit Rohit
Verified Expert in Engineering
Node.js Developer
Toronto, ON, Canada
Toptal member since February 13, 2025
Bio
Rohit is a senior back-end and full-stack engineer with 7+ years of experience building scalable Java Spring Boot microservices and event-driven systems. He has strong expertise in SQL and NoSQL databases and in deploying applications on AWS. He also works with AI agents, LLM integrations, and RAG pipelines. He has built high-scale platforms handling 3+ TB of data, delivering reliable and high-performance solutions.
Portfolio
Ngentix Inc.
Node.js, React, TypeScript, JavaScript, AI Model Integration, Agentic AI...
Productiv, Inc
TypeScript, SQL, JavaScript, Node.js, AI Model Integration, Agentic AI...
Clarity AI, LLC
RESTFul APIs, JavaScript, Node.js, AI Model Integration, Agentic AI, AI Agents...
Experience
- Spring Boot - 7 years
- Node.js - 7 years
- Amazon Web Services (AWS) - 7 years
- RESTFul APIs - 6 years
- Java - 6 years
- AI Integration - 3 years
- AI Agents - 2 years
- Agentic AI - 2 years
Preferred Environment
Node.js, Java, Spring Boot
The most amazing...
...thing I've built is LLM-powered automation workflows connecting Stripe, QuickBooks, Slack, and Gmail, enabling end-to-end task automation across SaaS platforms.
Work Experience
Node.js and React Developer
2025 - 2025
Ngentix Inc.
- Built LLM-powered automation workflows using Ollama and MCP to integrate Stripe, QuickBooks, Slack, and Gmail, enabling end-to-end task automation across SaaS platforms.
- Developed scalable back-end services in Node.js and TypeScript, powering AI-driven automation pipelines and enterprise integrations.
- Designed secure multi-tenant credential storage for hundreds of connectors, handling OAuth tokens and API keys with encrypted access patterns.
- Implemented RAG-based data retrieval pipelines using vector databases to deliver accurate, context-aware responses across enterprise data sources.
- Optimized system performance and reliability to support high-volume automation workflows and real-time processing.
- Collaborated on CI/CD pipelines and AWS deployments, enabling automated testing, staging releases, and scalable infrastructure.
- Contributed to React and Tailwind UI components, ensuring seamless integration between back-end automation logic and user workflows.
Technologies: Node.js, React, TypeScript, JavaScript, AI Model Integration, Agentic AI, AI Agents, Large Language Models (LLMs), Amazon S3 (AWS S3), Amazon DynamoDB, AI Integration, Amazon Web Services (AWS), Next.js, MongoDB, Python, Amazon OpenSearch, Material UI, Quarkus, Firebase, Elasticsearch, Android, Kotlin, Microservices, Spring Boot, Sitecore, Sitecore Experience Manager Cloud (XM Cloud), Redux, Express.js, Web Security, CSS, Large-scale Projects, Web Development, Artificial Intelligence (AI), Full-stack, WebSockets, Back-end, Software Development, AI Model Training, Code Review, AI Modeling, APIs, QuickBooks API, QuickBooks Desktop, Intuit QuickBooks, REST APIs, API Backwards Compatibility, AI Automation, AI Agent Orchestration, Front-end, LLM Agents, Amazon Bedrock AgentCore, Oracle Integration Cloud (OIC), Claude Code, Product Frameworks, Product Management
AWS/Back-end Developer
2025 - 2025
Productiv, Inc
- Developed scalable back-end APIs using Node.js and TypeScript, supporting core business logic for a SaaS platform.
- Designed and implemented serverless workflows using AWS Lambda, SQS, and Step Functions to enable asynchronous processing and improve system scalability.
- Built and optimized data pipelines to handle large volumes of application data, ensuring efficient processing and reliability.
- Improved system performance and scalability by optimizing API design and data flow across distributed services.
- Collaborated with cross-functional teams to design and deliver high-quality features aligned with business requirements.
- Developed responsive front-end components using Next.js, ensuring smooth user experience and seamless integration with back-end services.
- Implemented CI/CD pipelines to automate testing and deployment, improving release efficiency and system reliability.
- Ensured secure API communication by implementing authentication and authorization mechanisms using modern best practices.
Technologies: TypeScript, SQL, JavaScript, Node.js, AI Model Integration, Agentic AI, AI Agents, Large Language Models (LLMs), Amazon S3 (AWS S3), Amazon DynamoDB, AI Integration, Amazon Web Services (AWS), Next.js, MongoDB, Python, Material UI, Quarkus, Firebase, Elasticsearch, Android, Kotlin, Microservices, Spring Boot, Sitecore, Redux, Express.js, Web Security, CSS, Large-scale Projects, Web Development, Artificial Intelligence (AI), Full-stack, WebSockets, Back-end, Software Development, AI Model Training, Code Review, AI Modeling, APIs, REST APIs, API Backwards Compatibility, AI Automation, AI Agent Orchestration, Front-end, LLM Agents, Amazon Bedrock AgentCore, Oracle Integration Cloud (OIC), Claude Code, Product Frameworks, Product Management
Back-end Node.js/Python Developer
2025 - 2025
Clarity AI, LLC
- Built an AI-powered contract analysis workflow using AWS Lambda to process music contracts and extract key information such as artist details, royalty terms, ownership, and advance payments.
- Designed LLM-based extraction logic to convert unstructured legal documents into structured, queryable data.
- Integrated AI models with document processing pipelines to automate contract understanding and reduce manual review effort.
- Developed scalable APIs to enable real-time contract uploads, processing, and retrieval of extracted insights.
- Implemented DynamoDB and S3-based storage for efficient handling of contract data and extracted metadata.
- Improved processing efficiency and reduced turnaround time for contract analysis through automated AI-driven workflows.
- Collaborated with stakeholders to define extraction requirements and ensure accuracy of contract interpretation.
Technologies: RESTFul APIs, JavaScript, Node.js, AI Model Integration, Agentic AI, AI Agents, Large Language Models (LLMs), Amazon S3 (AWS S3), Amazon DynamoDB, AI Integration, Amazon Web Services (AWS), Next.js, MongoDB, Python, Material UI, Quarkus, Firebase, Elasticsearch, Android, Kotlin, Microservices, Spring Boot, Sitecore, Sitecore Experience Manager Cloud (XM Cloud), Redux, Express.js, Web Security, CSS, Large-scale Projects, Web Development, Artificial Intelligence (AI), Full-stack, WebSockets, Back-end, Software Development, AI Model Training, Code Review, AI Modeling, APIs, REST APIs, API Backwards Compatibility, AI Automation, AI Agent Orchestration, Front-end, LLM Agents, Amazon Bedrock AgentCore, Oracle Integration Cloud (OIC), Claude Code, Product Frameworks, Product Management
Senior Software Developer
2025 - 2025
Autodesk
- Led the development of a large-scale search platform handling 3+ TB of data using Spring Boot, DynamoDB, and OpenSearch.
- Built and optimized custom search queries and indexing strategies, improving performance and ensuring low-latency responses.
- Developed scalable microservices to process large volumes of structured and unstructured data efficiently.
- Resolved OpenSearch indexing failures and implemented retry mechanisms to ensure data consistency and system reliability.
- Designed DynamoDB schemas using GSIs, TTL, and Streams to enable efficient data access and real-time indexing pipelines.
- Implemented data ingestion pipelines from DynamoDB to OpenSearch, ensuring validation and index consistency.
- Wrote unit and integration tests for search queries, improving system reliability and reducing production issues.
Technologies: AI Model Integration, Amazon S3 (AWS S3), Amazon DynamoDB, AI Integration, Amazon Web Services (AWS), Next.js, Amazon OpenSearch, Elasticsearch, Microservices, Spring Boot, Java, Event-driven Architecture, Sitecore Experience Manager Cloud (XM Cloud), Express.js, Web Security, CSS, Large-scale Projects, Web Development, Artificial Intelligence (AI), Full-stack, WebSockets, Back-end, Software Development, Large Language Models (LLMs), AI Model Training, Code Review, AI Modeling, APIs, REST APIs, XML, API Backwards Compatibility, SSH, Go, Front-end, Claude Code, Product Frameworks, Product Management
Java Full-stack Developer
2023 - 2025
Brickred Systems
- Led a team of 6–10 developers to design and build scalable back-end systems using Java, Spring Boot, and a microservices architecture.
- Designed and implemented distributed systems to handle high-volume traffic, ensuring low latency and high availability.
- Developed RESTful APIs and back-end services to support core business functionalities across multiple applications.
- Architected and optimized data models using PostgreSQL and Redis to improve system performance and scalability.
- Implemented asynchronous processing using AWS SQS and event-driven architecture to enhance system reliability.
- Collaborated with cross-functional teams in Agile environments to deliver features aligned with business goals.
- Established CI/CD pipelines and deployment workflows, improving release efficiency and reducing deployment risks.
Technologies: Java, RESTFul APIs, Docker, JavaScript, PostgreSQL, Amazon S3 (AWS S3), Amazon DynamoDB, Amazon Web Services (AWS), Next.js, MongoDB, Python, Amazon OpenSearch, Material UI, Quarkus, Firebase, Elasticsearch, Android, Swift, iOS, Microservices, Spring Boot, Sitecore, Redux, Web Security, CSS, Large-scale Projects, Web Development, Full-stack, WebSockets, Back-end, Software Development, Code Review, APIs, REST APIs, XML, Linux, API Backwards Compatibility, SSH, Go, Front-end, Product Frameworks, Product Management
Java Engineer
2021 - 2022
Indigo
- Created reusable, modular, and efficient React components, leveraging custom hooks to manage component lifecycles.
- Built Java apps without servers using AWS Lambda. This allowed us to save money while apps could run when needed.
- Leveraged Amazon EKS to deploy and manage Java applications in a Kubernetes environment, ensuring applications could scale smoothly.
Technologies: SQL, Java, TypeScript, JavaScript, PostgreSQL, Amazon S3 (AWS S3), Amazon DynamoDB, Amazon Web Services (AWS), MongoDB, Python, Amazon OpenSearch, Material UI, Quarkus, Firebase, Elasticsearch, Android, Swift, iOS, Microservices, Spring Boot, Sitecore, Sitecore Experience Manager Cloud (XM Cloud), Redux, Web Security, CSS, Large-scale Projects, Web Development, Artificial Intelligence (AI), Full-stack, WebSockets, Back-end, Software Development, Code Review, APIs, REST APIs, Supabase, Linux, API Backwards Compatibility, SSH, Go, Front-end, Product Frameworks, Product Management
Java Engineer
2020 - 2021
HDFC Bank
- Leveraged Spring Boot's auto-configuration feature to automatically set up application parts based on project dependencies, reducing the need for manual setups and speeding up development.
- Integrated Azure services into software solutions, focusing on reliability, scalability, and maintainability.
- Developed and enhanced front-end layouts using React and APIs. I also used HTML, CSS, and Tailwind CSS to style the React components.
Technologies: RESTFul APIs, React, Java, Vercel, PostgreSQL, Amazon S3 (AWS S3), Amazon DynamoDB, Amazon Web Services (AWS), Python, Material UI, Quarkus, Firebase, Elasticsearch, Android, Swift, iOS, Microservices, Spring Boot, Sitecore Experience Manager Cloud (XM Cloud), Web Security, CSS, Large-scale Projects, Full-stack, WebSockets, Back-end, Software Development, Code Review, APIs, REST APIs, Supabase, XML, Linux, API Backwards Compatibility, Go, Front-end, Product Frameworks, Product Management
Experience
Senior Java Developer
I worked as a back-end developer on a large-scale search and data platform built using Java, Spring Boot, and microservices architecture. The system handled over 3+ TB of data and supported high-volume, low-latency search use cases. I designed and developed REST APIs and implemented an event-driven architecture using messaging systems to ensure scalability and reliability.
The platform used both SQL and NoSQL databases, including DynamoDB and OpenSearch, to efficiently manage structured and unstructured data. I deployed and maintained services on AWS, ensuring performance, monitoring, and fault tolerance in production.
I closely collaborated with front-end and cross-functional teams to deliver end-to-end features, optimize queries, and improve system performance, contributing to a highly scalable and production-ready solution.
The platform used both SQL and NoSQL databases, including DynamoDB and OpenSearch, to efficiently manage structured and unstructured data. I deployed and maintained services on AWS, ensuring performance, monitoring, and fault tolerance in production.
I closely collaborated with front-end and cross-functional teams to deliver end-to-end features, optimize queries, and improve system performance, contributing to a highly scalable and production-ready solution.
AI Financial Operations Agent (Multi-agent System)
https://ngentix.ai/• Designed and built an AI-powered multi-agent system to automate financial workflows, including invoice processing, data extraction, and SaaS integrations.
• Implemented multiple AI agents for document parsing, decision-making, and API execution, enabling automated actions such as syncing data with platforms like Stripe and QuickBooks.
• Built RAG-based pipelines using vector databases to allow context-aware querying of financial data and historical records.
• Developed scalable back-end services using Node.js and TypeScript, integrating AI workflows with REST APIs and cloud infrastructure.
• Leveraged AWS services for orchestration, storage, and processing to ensure reliability and scalability of agent-driven workflows.
• Implemented multiple AI agents for document parsing, decision-making, and API execution, enabling automated actions such as syncing data with platforms like Stripe and QuickBooks.
• Built RAG-based pipelines using vector databases to allow context-aware querying of financial data and historical records.
• Developed scalable back-end services using Node.js and TypeScript, integrating AI workflows with REST APIs and cloud infrastructure.
• Leveraged AWS services for orchestration, storage, and processing to ensure reliability and scalability of agent-driven workflows.
AI-powered Contract Intelligence System
https://clarity.ai/• Designed and built an AI-powered contract intelligence system to process music contracts and extract structured insights such as artist details, royalty terms, ownership, and payment information.
• Implemented an AWS Lambda-based pipeline with S3, DynamoDB, and API Gateway for scalable document processing.
• Integrated LLMs and AI models to convert unstructured legal documents into structured, queryable data, significantly reducing manual review effort.
• Implemented an AWS Lambda-based pipeline with S3, DynamoDB, and API Gateway for scalable document processing.
• Integrated LLMs and AI models to convert unstructured legal documents into structured, queryable data, significantly reducing manual review effort.
Scalable SaaS Platform (Node.js and AWS)
https://productive.io/• Developed a scalable SaaS platform with Node.js and TypeScript, building back-end APIs and business logic to support enterprise workflows.
• Designed distributed systems and integrated multiple third-party services to enable seamless data flow and automation.
• Built responsive front-end components using modern frameworks, ensuring high performance and smooth user experience.
• Designed distributed systems and integrated multiple third-party services to enable seamless data flow and automation.
• Built responsive front-end components using modern frameworks, ensuring high performance and smooth user experience.
Education
2017 - 2021
Bachelor's Degree in Information Technology
Guru Gobind Singh Indraprastha University - New Delhi, India
Certifications
JUNE 2020 - PRESENT
Java Developer
Coding Blocks
Skills
Libraries/APIs
React, Node.js, QuickBooks API, REST APIs
Tools
Amazon OpenSearch, Claude Code
Languages
Java, SQL, TypeScript, JavaScript, Python, CSS, XML, Go, Swift, Kotlin
Frameworks
Next.js, Material UI, Spring Boot, Redux, Express.js
Paradigms
Microservices, Event-driven Architecture
Platforms
Docker, Vercel, Amazon Web Services (AWS), Firebase, Android, Sitecore Experience Manager Cloud (XM Cloud), iOS, Linux, Oracle Integration Cloud (OIC), Ollama
Storage
MongoDB, Amazon S3 (AWS S3), PostgreSQL, Elasticsearch, Amazon DynamoDB, Redis, NoSQL
Other
RESTFul APIs, AI Integration, Large Language Models (LLMs), Artificial Intelligence (AI), Full-stack, Sitecore, Web Security, Large-scale Projects, Web Development, WebSockets, Back-end, Software Development, Code Review, AI Modeling, APIs, QuickBooks Desktop, Intuit QuickBooks, Supabase, API Backwards Compatibility, Front-end, Product Frameworks, Product Management, AI Agents, Agentic AI, AI Model Integration, Quarkus, AI Model Training, SSH, AI Automation, AI Agent Orchestration, LLM Agents, Amazon Bedrock AgentCore, Tailwind UI, API Integration, Vector Databases, Semantic Search, Retrieval-augmented Generation (RAG)
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