Senior Software Engineer

Meet Shyani

Dallas, TX • 469-***-**** • ***********@*****.*** • linkedin.com/in/shyanimeet1

Professional Summary

Software Developer with 7 years of hands-on experience designing, developing, and deploying Python-based backend applications, RESTful APIs, AI-enabled solutions, and data-driven applications. Strong expertise in Python, Flask, FastAPI, Django, SQL, Pandas, JSON, React, and cloud platforms including AWS and Azure. Experienced in developing intelligent automation workflows, integrating AI/GenAI capabilities, processing structured and unstructured data, and building scalable data pipelines. Skilled in Docker, Kubernetes, CI/CD automation, application monitoring, troubleshooting, performance optimization, Agile development, and translating business requirements into maintainable technical solutions. Technical Skills

Languages: Python, Java, JavaScript, SQL, PL SQL, JSON, YAML Frameworks: Flask, FastAPI, Django, React, Spring Boot, Beautiful Soup, Requests, REST APIs Cloud: AWS (Lambda, S3, RDS, Aurora, SQS, SNS, CloudWatch), Azure, Azure AI Foundry, Azure OpenAI, Azure Messaging: Kafka, Kinesis, RabbitMQ

Databases: PostgreSQL, MySQL, SQL Server, Snowflake, MongoDB, Redis, DynamoDB, Oracle, ElasticSearch, Cassandra OS/Environment: Linux/Unix, Git, GitHub

Security/Auth: Authentication, Authorization, Application Security DevOps/CI-CD: Docker, Kubernetes, Jenkins, GitHub Actions, Azure DevOps, Terraform, Ansible, GoCD, CI/CD Methodologies: Agile, Scrum, TDD, OOP, Design Patterns AI/Automation: Pandas, NumPy, GenAI, LLM Integration, Document Intelligence, RPA, Google ADK, Microsoft Power Automate Professional Experience

Senior Software Development Engineer(GenAI) Feb 2023 – Present Prudential Financial

• Designed and developed scalable Python backend applications and RESTful APIs using Flask and FastAPI, supporting high-volume enterprise applications and business workflows.

• Built and integrated REST APIs using JSON for secure data exchange between internal applications, third-party services, databases, and cloud-based systems.

• Developed Python-based ETL and data processing pipelines using Pandas, NumPy, and SQL, processing over 1TB of structured and unstructured data daily with 99.8% reliability.

• Integrated backend applications with PostgreSQL, MongoDB, and cloud-based data platforms, optimizing SQL queries and improving data retrieval and application performance.

• Developed AI and GenAI-enabled solutions using LLM technologies to automate document processing, information extraction, validation, and business workflows, reducing manual effort by 45%.

• Designed and implemented Retrieval-Augmented Generation (RAG) pipelines using Python, LLMs, embeddings, and vector databases to retrieve relevant enterprise knowledge and generate context-aware responses from large document repositories.

• Integrated LLM APIs with Python and FastAPI services, developing prompt engineering, context management, structured JSON outputs, validation, and fallback mechanisms to improve the accuracy and reliability of GenAI-powered applications.

• Built semantic search and document Q&A capabilities by generating vector embeddings, storing and retrieving document chunks through vector databases, and combining retrieved context with LLMs to support intelligent enterprise search and knowledge discovery.

• Integrated cloud-based AI services and document intelligence capabilities with Python applications to extract, process, validate, and transform information from enterprise documents.

• Collaborated with frontend teams to integrate React-based user interfaces and dashboards with Python REST APIs for real-time data visualization and workflow management.

• Containerized Python applications using Docker and deployed scalable services through Kubernetes-based environments.

• Built and maintained CI/CD pipelines using Jenkins, GitHub Actions, Azure DevOps, and YAML-based configurations to automate testing, build, and deployment processes.

• Implemented application monitoring, logging, and alerting using AWS CloudWatch to identify failures, troubleshoot issues, optimize performance, and maintain 99.9% system uptime.

• Performed root-cause analysis and resolved production issues across Python applications, APIs, databases, and distributed services in Linux environments.

• Collaborated with product, data, DevOps, and cross-functional teams in an Agile/Scrum environment to translate business requirements into scalable technical solutions.

• Performed code reviews and mentored a team of 6+ engineers on Python development, REST API design, OOP principles, and clean coding standards.

Software Engineer Apr 2018 – June 2021

American Airlines

• Developed and maintained backend applications and RESTful APIs using Python, Django, and Flask for customer-facing and internal airline applications.

• Built JSON-based REST API integrations connecting frontend applications, backend services, relational databases, and internal enterprise systems.

• Developed and optimized Python, Pandas, and SQL-based data pipelines on Linux/Unix systems to process and transform operational data.

• Designed and optimized SQL queries and PostgreSQL database schemas, improving application performance and reducing query execution times by 40%.

• Collaborated with frontend developers to integrate responsive web interfaces and dashboards with Python backend services and REST APIs.

• Developed Python-based utilities to automate repetitive data processing and operational workflows, improving efficiency and reducing manual effort.

• Integrated third-party and internal services through REST APIs, implementing data validation, exception handling, and logging for reliable data exchange.

• Built automated unit and integration tests using PyTest and Selenium, reducing defect escape rates by 30% and improving application quality.

• Containerized applications using Docker and built CI/CD pipelines using Jenkins and Git, reducing deployment times by 50% and supporting frequent releases.

• Monitored, troubleshot, and resolved application and data-processing issues in Linux environments to improve application stability and overall performance.

• Collaborated with developers, QA engineers, product owners, and business stakeholders in an Agile/Scrum environment throughout the software development lifecycle.

Projects

AI-Powered Document Intelligence Platform - Python, Flask, Azure OpenAI, Azure AI Document Intelligence, REST APIs, JSON, React, Docker Designed and developed an AI-powered document processing platform using Python, Flask, Azure OpenAI, and Document Intelligence to extract and process information from unstructured documents. Built RESTful APIs to transform extracted information into structured JSON, validate results, integrate downstream systems, and support a React-based interface for document review and workflow management. Intelligent Automation Workflow Orchestrator - Python, FastAPI, Pandas, SQL, Kafka, REST APIs, Docker, CI/CD Built an intelligent automation platform to streamline data-intensive business processes using Python, FastAPI, Pandas, SQL, and AI capabilities. Implemented workflow orchestration, data validation, exception handling, asynchronous processing, monitoring, and REST API integrations to improve operational efficiency and application reliability. AI Research Assistant using Google ADK - Python, Google ADK, Gemini API, RAG, REST APIs, ChromaDB, Streamlit Developed a learning-focused AI research assistant using Python and Google Agent Development Kit (ADK) to explore agent development, tool calling, and LLM-based workflows. Created an ADK agent powered by Gemini that can answer user questions, invoke custom Python tools, summarize research content, and retrieve information from uploaded documents using a basic RAG pipeline. Implemented document chunking, embeddings, and vector search with ChromaDB and built a simple Streamlit interface for interacting with the assistant.

Certifications

AWS Certified Solutions Architect – Professional Amazon Web Services 2026 AWS Certified Solutions Architect – Associate Amazon Web Services 2026 AWS Certified DevOps Engineer – Professional (DOP-C02) LinkedIn 2025 Generative AI: Working with Large Language Models LinkedIn 2025 Machine Learning A-Z: AI, Python & R Udemy 2023

Education

University of the Cumberlands Aug 2029

PhD in Artificial Intelligence

University of Missouri–Kansas City Dec 2022

M.S. Computer Science

Gujarat Technological University May 2018

B.E. Computer Engineering

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