Aakash Vashishtha

Software Development Analyst

AWS (AppSync, ECS), GoLang, ReactJS, Docker, Python (LangChain), JSX, RabbitMQ, Jira, Postgres

• Spearheaded migration to React, and implemented ADA compliance, enhancing overall accessibility.
• Developed ProxyAI using GPT-4 API, automating 60% of data entry tasks, leading to a 15% increase in user engagement.
• Engineered APIs and front-end solutions for SSO data management, improving admin workflow efficiency by 40%
• Wrote GUI testing scripts for the activities section validating the component flow of the platform.
• Implemented AWS AppSync monitoring, reducing subscription incidents by 50% and optimizing API usage.
• Wrote APIs for email logs making it easier for admins to track bugs reported by customers.

Capstone Project

Python (flask, LangChain),FAISS, RAG, ReactJS, Docker, MySql

• Developed a Flask-LangChain-based system to fetch and analyze Reddit/X posts.
• Implemented a RAG pipeline to compare fetched posts with user-stored products in FAISS.
• Integrated ChatGPT and DeepSeek to generate human-like responses for engagement.
• Built an automated system to post AI-generated responses back on Reddit/X.
• Developed a ReactJS frontend for seamless user interactions and managed MySQL in a Dockerized setup.

Software Developer II

Stack : AWS (Step Function, Cloudwatch, Athena, Glue, Lambda), Python (Boto3, Pyspark), Postgres, Jfrog, Java(Spring Boot), RabbitMQ

Worked on the backend of an e-commerce website using Java Spring Boot and Netflix Eureka as a part of training.

• Implemented using microservice architecture, created the cart and orders microservice.
• Deployed the Microservices and the database on GCP.

Worked on Ingest and Publishing for organization authority in Thomson Reuters.

• Modified Ingest Step Function to increase max concurrency for ingestion glue jobs, increasing the efficiency of Ingest step function and reducing the execution time significantly.
• Performed data validation and preprocessing to standardize the data ingested in the tables.
• Created Glue jobs to generate reports (naics/country/sic/partition) of the organizations and stored it in s3 to feed it to the API facing the customers as well as notifying them when a new report was generated through SNS.
• Wrote test cases and brought test coverage from 7% to 80% for the whole Gcs publishing repo. Found a bug which was causing the publishing glue job to fail constantly and was being worked on by the colleagues. I Pointed out the exact issue and got it fixed.
• Spearheaded the implementation of spark executor logs for all Glue jobs, addressing a long-standing issue adopted across Org Authority Team repositories.
• Engineered organization ID mappings in PostgreSQL via PySpark, optimizing performance and transitioning to a shared library for streamlined use.

Led a 4-member team in integrating Dragos on an AWS Outpost server with Greengrass, developing an end-to-end data pipeline for insightful AWS Quicksight reports, utilized as a POC for clients like Shell and Koch.

Platform Engineer

Stack : Terraform, AWS (EC2, Eventbridge, EMR, Athena, Glue, Lambda), Python (Boto3, Pyspark), HiveQL, Kafka

Migrated the current infrastructure to IaC (Infrastructure as Code) using Terraform & Chef.

• New setup now allows various features such as spinning up Redshift, EMR & Kubernetes clusters.
• All applications now run on Chef bootstrapped servers created using terraform with additional support for AWS auto-scaling and AWS load balancing (both ALB & ELB).

POC of next gen Data Lake architecture using Terraform. PoC was a success and was adopted for org wide usage.

• Ran Glue crawler and EMR jobs (pyspark and hiveql queries in master node) to benchmark efficiency on 125 GB data.
• Ran Glue jobs & Athena queries on the schema created by Glue crawler, documented the steps to be used in the new setup.
• Increased the availability of the system by automating fallback to backup clusters when emr-targets are unhealthy (AWS Lambda, network-LB, Boto3).
• Created an email based notification service on a serverless architecture (Lambda, EventBridge and SNS) to notify the team when an EMR cluster terminates and a backup cluster gets activated.

Software Engineering Intern

Stack : Python (Django), MySQL, JS/Bootstrap5

Report Manager - A web-app to automate the record of ticket-approvals. Team now doesn’t have to store emails in excel sheets manually, excel/pdf/zip files were created on demand. Emails were parsed and stored in mysql tagged with subject for easy querying. Bitlocker - Inventory management app that keeps track of the company assets given to the employees.

Software Engineering Intern

Stack : ElectronJS, Bootstrap5, SQL/Websql

Created the front end and windows exec (electronJS) of POS (Point Of Sale) website, worked on state management using client side cookies (WebSQL, Js). Used webSql to store the data offline and synced it with the database when the user came online.

Arizona State University, Tempe

GPA: 3.7/4.0

Manipal Institute of Technology, Manipal

CGPA: 8.30/10.0

Data Vizualization:

Developed a Python-based machine learning model using Ridge Regression to analyze and predict calorie content in dishes, classify them into appropriate fad diets, and identify potential nutritional deficiencies. Implemented data-driven visualizations, including calories vs. carbs and FDA-recommended vs. actual daily vitamin intake, providing insights into diet trends and health impacts.

Unity Game:

Developed a taxi simulation game where players navigate the city to pick up and drop off passengers while racing against time. Implemented reckless driving detection that triggers police chases, along with evasion mechanics, health management, and power-ups for strategic gameplay.

Springboot App:

Developed ScrumPlay, a team-based Scrum simulator using Spring MVC and Java Swing. Mimicking a Microsoft Azure environment, users engage in sprints, scrum calls, and sprint planning meetings, allowing dynamic modifications to user stories. The application fosters collaborative project management, generating insightful burndown charts post each sprint.

Android App:

A Java app for buying showpieces which uses AR (Google AR-Core) and allows users (user profile: Firestore) to visualise the item in their homes before actually buying it.

Data Mining:

Implemented the paper “Attention is all you need” to translate between Hindi and English Sentences. Used IIT Bombay English-Hindi Corpus as a dataset and divided it to obtain training dataset, word embeddings were created using Facebook’s fast-text.

Java game:

An Object finding game that uses template matching (Java OpenCV) where users have to find the given objects in a crowded background photo as fast as possible to beat the leaderboard (MySQL on AWS EC2).

C# App:

A tour management tool where users can see interesting destinations on the maps, users can book hotels, leave reviews for hotels. They can also book tour guides and tour packages, app used Oracle SQL database and C# for front and back end.

IOS App:

App (Swift) allows first responders to get the details of a user's allergies and details (firestore database) in an accident via an id stored on their NFC card (CoreNFC). Android users will be directed to a webpage (AngularJS).

WebApp:

Led a team of 3 people to develop a web-app to predict occurrence of floods; notify users & emergency contacts and show nearest relief camp locations. Web-app (VueJS), User profile (MongoDB), geo-location queries (Websql), location heatmaps (HeatmapJS, GoogleMap API), weather data (Accuweather APIs).

Robotics:

RUGVED Systems is a student based team committed to designing autonomous robots with cutting edge artificial intelligence. I was a member of AI subsystem and worked on simulations & lane detection.

• Simulated the IGVC ground and the RUGVED autonomous vehicle using ROS design engine, Gazebo, ran simulations using the actual measurements of the vehicle to test the trajectory of the vehicle using a 3D visualization tool Rviz.
• Wrote code for Lane Detection by filtering out the camera feed on RUGVED using python OpenCV.

CLI App:

CLI app using sockets that sends messages to users authenticated via their Git accounts over terminal.