AI Engineer | Full Stack Engineer | LLM Systems | Agentic AI | RAG · Antioch, CA
About
AI Engineer and Full Stack Engineer with nearly 7 years of progressive experience spanning software engineering, full-stack development, data engineering, machine learning, MLOps, Generative AI, RAG, and agentic AI.
Experience
AI Full Stack Engineer — Next Generation Innovation (NGI)
Engineer end-to-end enterprise AI applications combining LLM services, Python backend APIs, modern frontend interfaces, enterprise data stores, and cloud infrastructure
Translate complex business requirements into AI solution architectures covering RAG pipelines, agentic workflows, API services, security, observability, and production deployment
Implement modular LangChain-based components for prompt execution, retrieval, tool integration, function invocation, and reusable LLM application workflows
AI Automation Engineer — Connecticut Claims Adjusters LLC
Engineered Python-based automation solutions that combined business rules, data processing, analytics, and intelligent decision-support capabilities
Translated operational requirements into scalable automation workflows designed to reduce manual processing and improve business efficiency
Developed reusable Python components for data ingestion, validation, transformation, enrichment, and downstream reporting.
AI Engineer / Prompt Engineer — University New Haven
Engineered enterprise RAG applications using Python, LangChain, OpenAI APIs, embeddings, semantic retrieval, and vector databases
Designed reusable LangChain prompt and retrieval components supporting grounded question answering and conversational AI workflows
Developed agentic workflows integrating contextual retrieval, tool calling, function calling, prompt orchestration, and multi-step reasoning
Full Stack / Data Engineer — Sun Technologies
Developed enterprise backend services and data applications using Python, SQL, APIs, distributed processing, and database technologies
Built reusable backend components supporting application integrations, data processing, and enterprise workflow requirements
Implemented scalable ETL/ELT processing using Python, SQL, Spark, and PySpark for high-volume enterprise datasets
Full Stack / Data Application Engineer — Chakra IT Solutions
Developed enterprise applications combining frontend interfaces, backend services, relational databases, analytics, and workflow automation
Built backend functionality using Python, Java, SQL, and REST APIs to support business application requirements
Automated reporting and data-processing activities using Python, Pandas, and NumPy
Skills
AI Engineering & Generative AI
Generative AI
LLM Applications
Retrieval-Augmented Generation (RAG)
Agentic AI
AI Agents
LangChain
LangGraph
LlamaIndex
GPT-4
Claude
Llama
Ollama
Prompt Engineering
Context Engineering
Tool Calling
Function Calling
Multi-Agent Orchestration
Conversational AI
Semantic Search
Document Intelligence
LLM Evaluation
MCP Integrations
Programming Languages
Python
Java
JavaScript
TypeScript
SQL
Full Stack Engineering
React
Next.js
FastAPI
Django
REST APIs
GraphQL
Microservices
Backend Development
Frontend Development
API Integration
Asynchronous Processing
OAuth
RBAC
Cloud & DevOps
Microsoft Azure
Azure OpenAI
Azure AI Search
Azure App Service
Azure Functions
Azure Blob Storage
Azure Key Vault
Azure DevOps
Azure Kubernetes Service (AKS)
Docker
Kubernetes
Terraform
Git
GitHub Actions
Jenkins
CI/CD
MLflow
Model Registry
Experiment Tracking
Prometheus
Grafana
Data Engineering
PostgreSQL
SQL Server
MySQL
SQLite
Redis
Apache Spark
PySpark
Hadoop
Hive
Kafka
Airflow
ETL/ELT
Data Warehousing
Dimensional Data Modeling
Education
Master of Science, Data Science — University of New Haven
Bachelor of Technology, Electronics and Communication Engineering — National Institute of Technology (NIT) Silchar
