Full Stack Python Developer - GenAI RAG

Rajasri Gavini

Full Stack Python Developer Django FastAPI Microservices GenAI

+1-409-***-**** ***************@*****.***

Professional Summary

•Full Stack Python Developer with 6+ years of experience, including hands-on production experience building GenAI, RAG, and LLM-powered applications across banking, fintech, healthcare, and enterprise environments.

•Experienced in developing production RAG solutions using LangChain, LangGraph, OpenAI, Azure OpenAI, pgvector, FAISS, and Sentence Transformers for document intelligence, semantic search, and contextual question answering.

•Strong expertise in end-to-end RAG architecture, including document ingestion, chunking, embedding generation, vector indexing, metadata filtering, hybrid retrieval, prompt orchestration, and LLM-based response generation.

•Hands-on experience building Agentic AI workflows using LangGraph, tool calling, conditional routing, intent classification, structured outputs, and MCP-based integration patterns for connecting LLM applications with enterprise APIs and data sources.

•Strong backend development experience using Python, FastAPI, Django, PostgreSQL, Redis, async processing, Docker, Kubernetes, REST APIs, and cloud-native deployment practices.

•Experienced in designing secure and production-ready AI applications with OAuth 2.0, JWT, RBAC, API validation, monitoring, CI/CD, and production support.

Education

Lamar University Aug 2024 – Dec 2025

Master’s in information systems GPA: 3.9/4.0 Beaumont, TX

Technical Skills

• Programming & Backend: Python, SQL, FastAPI, Django, Flask, REST APIs, Microservices, Async Python, SQLAlchemy, Pydantic

• AI / GenAI: OpenAI, Azure OpenAI, LangChain, RAG, Prompt Engineering, Embeddings, Vector Search, Semantic Search, Structured Outputs

• Agentic AI: LangGraph, Tool Calling, Multi-Step LLM Workflows, Intent Classification, Tool Orchestration, MCP

• Databases & Caching: PostgreSQL, pgvector, MySQL, MongoDB, Redis, SQL Optimization, Indexing

• Messaging & Processing: Kafka, RabbitMQ, Celery, ETL Pipelines, Pandas, NumPy

• Cloud & DevOps: AWS, GCP, Docker, Kubernetes, GitHub Actions, Jenkins, Terraform, CI/CD

• Security: OAuth 2.0, OIDC, JWT, SSO, RBAC, IAM

• Frontend: React.js, React Hooks, Redux Toolkit, Next.js, TypeScript, JavaScript

• Testing & API Tools: PyTest, unittest, Postman, Swagger/OpenAPI

Experience

HSBC

Full Stack Python Developer(Gen AI) Remote

Jan 2026 – Present

•Designed and developed scalable backend services using Python and FastAPI, implementing asynchronous REST APIs, reusable service layers, Pydantic validation, and structured exception handling for banking and GenAI workflows.

•Developed responsive financial dashboards using React.js, TypeScript, Redux Toolkit, and React Hooks, integrating transaction and AI-generated data with efficient state management and error handling.

•Designed relational and semantic data storage solutions using PostgreSQL, pgvector, and Redis, implementing optimized schemas, vector indexing, metadata filtering, and caching for financial document retrieval.

•Built Retrieval-Augmented Generation workflows using LangChain, OpenAI, prompt engineering, embeddings, semantic search, and structured outputs for contextual financial document intelligence.

•Containerized enterprise applications using Docker and deployed services on Kubernetes and GCP using Cloud Run, Cloud SQL, Cloud Storage, and IAM for secure and scalable deployments.

•Built a LangGraph-based multi-step agent workflow with intent classification, document retrieval, SQL query execution, and response synthesis, enabling dynamic tool selection across enterprise data sources.

•Implemented MCP-based integration patterns to connect LLM workflows with internal APIs, document repositories, and transaction data sources using structured tool schemas and controlled context exchange.

•Developed secure applications using Django and Django REST Framework, implementing OAuth 2.0, JWT, RBAC, audit logging, and API authorization for sensitive banking workflows.

•Built enterprise data-processing pipelines using Pandas, NumPy, SQL, and Apache Kafka to validate, transform, enrich, and stream financial transaction data across distributed systems.

•Developed Agentic AI workflows using Lang Graph, tool calling, intent classification, dynamic tool selection, and multi-step decision logic for automated document and financial query processing.

•Implemented asynchronous processing using FastAPI, Celery, and RabbitMQ for long-running AI and document-processing tasks with retry handling, background execution, and reliable messaging.

•Built document ingestion workflows using custom loaders and RecursiveCharacterTextSplitter to process PDF and DOCX files while preserving document metadata for downstream retrieval.

•Optimized PostgreSQL queries, indexing strategies, connection management, and Redis caching to improve reporting, transaction search, and semantic document retrieval performance.

•Developed GenAI proof-of-concept solutions using Azure OpenAI, FAISS, Sentence Transformers, and vector embeddings for semantic search and enterprise knowledge-retrieval use cases.

•Developed modular backend components using Flask, SQLAlchemy, and Pydantic for reusable business logic, database integration, request validation, and third-party API connectivity.

•Enhanced AI document workflows using LangChain, OpenAI function calling, pgvector retrieval, and metadata-aware search to route requests between semantic search, SQL data access, and internal services.

•Automated testing and deployment using PyTest, GitHub Actions, Jenkins, Docker, Kubernetes, and GCP pipelines to support reliable CI/CD and production releases.

Lamar University

Python Developer Beaumont, TX

Oct 2024 – May 2025

•Developed Python-based research applications using Pandas and NumPy to clean, validate, transform, and prepare structured academic datasets for analysis and reporting.

•Designed REST APIs using FastAPI, Pydantic, and SQLAlchemy to support secure data access, request validation, and reliable integration with PostgreSQL databases.

•Built RAG workflows using LangChain, OpenAI, embeddings, and pgvector to enable semantic search, contextual document retrieval, and intelligent answering across research documents.

•Developed a proof-of-concept RAG system using LangChain, OpenAI embeddings, pgvector, and Sentence Transformers to support semantic search and contextual retrieval across academic research documents.

•Containerized applications using Docker and deployed services on Kubernetes while supporting CI/CD pipelines, application monitoring, and scalable academic research workloads.

Cognizant Technology Services

Full stack Python Developer

Hyderabad, India May 2022 – Aug 2024

Developed scalable backend services using Python and Django, implementing reusable business logic, request validation, exception handling, and secure enterprise workflows.

Built responsive frontend applications using React.js and TypeScript, implementing reusable components, Hooks, form validation, and dynamic user interactions.

Designed and optimized PostgreSQL schemas, SQL queries, indexing strategies, and transaction handling to improve application performance and reporting efficiency.

Developed RESTful microservices using FastAPI and Pydantic, implementing asynchronous processing, request validation, pagination, and standardized API responses.

Implemented event-driven processing using Apache Kafka and Redis to support asynchronous messaging, caching, retry handling, and distributed application workflows.

Containerized Python applications using Docker and deployed scalable workloads on Kubernetes, supporting consistent environments and reliable production deployments.

Developed secure application workflows using OAuth 2.0 and JWT, implementing authentication, role-based access control, protected routes, and API authorization.

Built enterprise data ingestion and transformation pipelines using Python, Pandas, and SQL to validate, cleanse, transform, and process operational datasets.

Developed AI-powered document workflows using LangChain, OpenAI, and MCP concepts, integrating contextual retrieval, tool interaction, prompt orchestration, and structured LLM responses.

Deployed cloud-native services on GCP using Cloud Run, Cloud Storage, and IAM, supporting secure application hosting, scalable deployments, and controlled resource access.

•Jr Python Developer Jun 2020– April 2022

•Developed backend systems and REST APIs using Python, Flask, and Django to support enterprise web applications, internal tools, and data-driven business workflows.

•Built data processing and ETL pipelines using NumPy, Pandas, and SQL to automate reporting, data validation, and operational data transformation tasks.

•Integrated third-party APIs and payment gateway services, implementing request validation, authentication handling, retry logic, and error management.

•Partnered with cross-functional teams to analyze business requirements, debug application issues, and deliver backend enhancements aligned with client expectations.

Certifications

AWS Certified Developer – Associate

Microsoft Power Platform Fundamentals PL-900

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