Summary:

• Automation Engineer with 5+ years of backend and integration experience, specializing in workflow automation, API orchestration, and system integrations.
• Hands-on experience designing and maintaining automation workflows using n8n, focusing on backend logic, triggers, and data flow orchestration.
• Strong expertise in REST APIs, Webhooks, JSON handling, and authentication mechanisms (OAuth, API keys, tokens).
• Proficient in JavaScript-based custom logic inside workflows for data transformation, validation, and conditional execution.
• Experienced in database-driven automations involving MySQL, PostgreSQL, and MongoDB for read/write operations.
• Skilled in deploying and maintaining self-hosted automation systems using Docker and cloud platforms.
• Comfortable working in SaaS and fast-paced startup environments, collaborating closely with backend, product, and business teams.

Skills:

• Automation & Workflow: n8n (Workflow Design, Triggers, Error Handling, Logging)
• Programming / Scripting: JavaScript (Custom n8n Logic), Python
• APIs & Integrations: REST APIs, Webhooks, JSON
• Authentication & Security: OAuth 2.0, API Keys, Token-based Auth
• Databases: MySQL, PostgreSQL, MongoDB
• Data Processing: Data Transformation, Mapping, Validation, ETL Workflows
• Other: ETL Pipelines, Document Intelligence, Time Series Forecasting, Recommendation Systems

Key Responsibilities:

Automation & Workflow Development (n8n)

• Designed, built, and maintained end-to-end automation workflows using n8n, focusing on backend logic and system integrations.
• Implemented trigger-based workflows using webhooks, scheduled jobs, and event-driven executions.
• Developed custom JavaScript logic inside n8n for data transformation, validation, conditional routing, and error handling.

API Integrations & Backend Orchestration

• Integrated third-party tools and internal systems using REST APIs, webhooks, and JSON-based payloads.
• Implemented secure authentication mechanisms including OAuth 2.0, API keys, and token-based access.
• Built workflow-driven orchestration for multi-system data synchronization and business process automation.

Data Processing & Database Operations

• Handled data mapping, normalization, and validation within automation workflows.
• Performed database read/write operations from n8n workflows using MySQL, PostgreSQL, and MongoDB.
• Built automation pipelines for ETL-style data extraction, transformation, and loading processes.

Reliability, Error Handling & Monitoring

• Implemented robust error handling, retries, fallback logic, and execution logging within workflows.
• Monitored workflow performance and failures to ensure high reliability in production environments.
• Improved automation stability by identifying bottlenecks and optimizing workflow execution paths.

Deployment, Cloud & DevOps

• Deployed and managed self-hosted n8n instances using Docker in cloud environments (AWS / Azure / GCP).
• Integrated automation workflows with CI/CD pipelines for version-controlled deployments.
• Worked in Linux-based environments to maintain automation infrastructure and services.

Collaboration & Ownership

• Collaborated closely with backend, product, and business teams to convert manual processes into automated workflows.
• Took ownership of automation solutions from design → development → deployment → maintenance.
• Worked independently in ambiguous problem spaces with a strong ownership and delivery mindset.

Projects:

Google Gemini GYM

Description:

Google Gemini GYM is an LLM evaluation and orchestration platform designed to benchmark and compare multiple LLM providers (Gemini, OpenAI, Claude). The system heavily relies on automation workflows, API integrations, asynchronous job execution, and data pipelines to manage large-scale evaluations, analytics ingestion, and reporting in a cloud environment.

Technologies Used: n8n (Workflow Logic), REST APIs, Webhooks, JavaScript, Python, FastAPI, BigQuery, Redis, Celery, Docker, CI/CD, LLM APIs (Gemini/OpenAI/Claude)

Roles & Responsibilities:

• Designed and implemented automation workflows to orchestrate LLM evaluation jobs across multiple providers.
• Integrated external LLM APIs (Gemini, OpenAI, Claude) using REST APIs and secure authentication.
• Built trigger-based and event-driven execution flows for model evaluation using asynchronous workers.
• Automated data ingestion and transformation pipelines for analytics storage in BigQuery.
• Implemented retry logic, error handling, and execution logging for long-running evaluation workflows.
• Managed workflow configuration using environment-based execution and parameterized inputs.
• Containerized automation services and deployed them via Docker and CI/CD pipelines.
• Collaborated with backend and analytics teams to automate benchmarking and reporting processes.

RAG Chatbot for Business Knowledge Extraction

Description:

An automation-driven RAG system designed to process enterprise documents, trigger ingestion workflows, generate embeddings, store vectors, and serve intelligent responses using LLMs. The project focused on workflow orchestration, data transformation, and system integration.

Technologies Used: n8n, JavaScript, REST APIs, Webhooks, Python, FastAPI, Hugging Face, Qdrant, OpenAI APIs

Roles & Responsibilities:

• Built automated document ingestion workflows triggered via APIs and webhooks.
• Orchestrated embedding generation, vector storage, and retrieval workflows.
• Integrated LLM APIs for summarization and entity extraction.
• Automated data validation, chunking, and metadata enrichment processes.
• Designed API-driven workflows for query routing and response generation.
• Implemented error handling, retries, and workflow monitoring to ensure reliability.
• Coordinated between storage, vector DB, and LLM systems using automation logic.

Generative AI Recipe & Insights Recommender (EAT App)

Description:

A recommendation platform that uses automation workflows to process user inputs, extract ingredients, perform vector similarity searches, and generate personalized insights using LLMs. Automation played a key role in data flow orchestration and API-based processing.

Technologies Used: n8n, JavaScript, REST APIs, Python, FastAPI, Qdrant, MongoDB, GPT-4.1 Nano, Azure, Docker

Roles & Responsibilities:

• Designed workflow-based pipelines to process user requests and trigger recommendation logic.
• Integrated LLM APIs for ingredient extraction and pairing recommendations.
• Automated vector similarity search workflows using Qdrant.
• Built API-triggered workflows for real-time recommendations.
• Automated database read/write operations for user preferences and history.
• Deployed and monitored workflows using Docker-based cloud environments.

Stock Prediction & Business Forecasting System

Description:

A data-driven forecasting system where automation workflows manage data ingestion, model execution, retraining triggers, and result publishing for business insights.

Technologies Used: n8n, Python, REST APIs, InfluxDB, Pandas, Azure, CI/CD

Roles & Responsibilities:

• Automated time-series data ingestion and preprocessing workflows.
• Triggered model execution and retraining using scheduled and event-based workflows.
• Orchestrated data flow between storage, ML models, and visualization layers.
• Implemented failure handling and logging for long-running forecasting jobs.
• Deployed automation pipelines on cloud infrastructure with CI/CD.

Multi-Context AI Assistant (Generative AI)

Description:

A multi-domain AI assistant powered by automated workflows that route queries across different knowledge bases and LLMs. The project emphasized workflow logic, API orchestration, and integration automation.

Technologies Used: n8n, JavaScript, REST APIs, Webhooks, Python, FastAPI, Qdrant, GPT-4.1, Twilio API, GraphQL

Roles & Responsibilities:

• Built workflow-based routing logic for multi-context conversations.
• Automated vector search and context retrieval workflows.
• Integrated LLM APIs for response generation and prompt chaining.
• Implemented WhatsApp-based triggers using Twilio webhooks.
• Automated feedback and improvement loops for personalization.
• Monitored and optimized workflow performance.

Document Intelligence & Business Entity Extraction

Description:

An automation-first document intelligence system that processes PDFs and enterprise documents through ingestion, extraction, summarization, and insight generation workflows.

Technologies Used: n8n, JavaScript, REST APIs, Python, FastAPI, Hugging Face, OpenAI APIs, Azure, Docker, CI/CD

Roles & Responsibilities:

• Built automated document processing workflows triggered via APIs.
• Integrated NLP and LLM APIs for summarization and entity extraction.
• Automated data validation and structured output generation.
• Designed REST-based workflows for enterprise system integration.
• Deployed and maintained workflows using Docker and CI/CD pipelines.
• Benchmarked and monitored automation accuracy and performance.