Vaibhav Singhal Profile Photo

Vaibhav Singhal

Software Engineer



Arizona State University, Tempe, Arizona

Master’s of Science & Engineering
Software Engineering
Aug. 2018 – May 2020

Guru Gobind Singh Indraprastha University, Delhi, India

Bachelor's of Technology
Computer Science
Aug. 2014 – June 2017

Guru Nanak Dev Institute of Technology, Delhi, India

Associate Degree
Electronics & Communications Engineering
Aug. 2011 – May 2014



  • Cloudera Certified Associate Spark and Hadoop Developer (CCA-175)
  • PythonInstitute Certified Associate in Python Language (PCAP-31-02)
  • Oracle Certified Associate in Database SQL (1Z0-071)
  • Google Associate Cloud Engineer

Udemy Certificates

  • Data Warehouse - The Ultimate Guide
  • Software Architecture & Design of Modern Large Scale Systems
  • Micronaut - cloud native microservices with Java
  • GCP Associate Cloud Engineer - Google Cloud Certification
  • Spark and Hadoop Developer - Python (PySpark)
  • Spark and Python for Big Data with PySpark
  • REST APIs with Flask and Python
  • Advanced REST APIs with Flask and Python
  • GCP: Complete Google Data Engineer & Cloud Architect Guide
  • Oracle SQL Developer From Scratch
Education Certificates

Technical Skills

  • Programming Languages: Python, Java, Bash, C/C++, SSML
  • Database: MySQL (SQLAlchemy), MongoDB (NoSQL) (MongoAlchemy), Redis, SQLite, Hive, Impala
  • Back-end: RESTful API (Micronaut, Flask), Apache Kafka, JWT (Tokens & Sessions for Security), uWSGI
  • GCP Services: GKE, Compute Engine, Load Balancing, Cloud Storage, Firestore, Cloud Build, Apigee, Deployment Manager
  • AWS Services: EKS, EC2, ELB, S3, DynamoDB, RDS, AWS CodeBuild, API Gateway, AWS CloudFormation
  • Big Data: Spark Streaming, Hadoop HDFS, Spark RDD & Data Frames APIs, Data Analysis, Sqoop, Apache Flume
  • Misc: GitLab CI/CD, Docker, Kubernetes, Gradle, OAuth, SAML, Scikit-Learn
  • Tools: Jmeter, Jira, Lucidchart, Swagger, Prometheus, Grafana, Agile with SCRUM, SDLC
Technical Skills ALT

Work Experience

LivePerson, Inc: Software Development Engineer

Jun. 2023 - Present (Toronto, ON, CA) | Jan. 2022 – Jun. 2023 (NYU, USA)

Architectural Expertise:
  • Developed a strategy to rebuild the connector service for seamless communication for internal services with conversational AI.
    • Implemented optimized data processing by leveraging Redis for fast lookups of brand configurations.
    • Results: A remarkable 40% reduction in data event size, subsequently leading to a 35% decrease in latency.
    • Technologies Utilized: Redis for caching, Java for backend logic, GCP (Google Cloud Platform) for cloud infrastructure, and APIgee for API management.
  • Optimized the VoiceCore key service to handle increasing concurrent calls efficiently.
    • Segregated the service into Text-to-Speech (TTS), Speech-To-Text (STT), and media microservices.
    • Implemented metrics for monitoring and alerting systems to detect and address issues proactively.
    • Results: Reduced system downtime by 25% and increased concurrent calls by 50%, scaling from 450 to 700 calls.
    • Technologies Utilized: Kafka for event streaming, Prometheus and Grafana for monitoring and alerting, GKE (Google Kubernetes Engine) for container orchestration, APIgee for API management, and GitLab CI/CD for continuous integration and deployment.
  • Led the design and development of the Audio File Management service to streamline customized voice audio files.
    • Created a robust storage and lookup system for audio blobs and Azure client keys using Google Cloud Storage and Redis.
    • Integrated Azure Text-to-Speech, enabling voice samples & customized audio file generation via SSML in a multi-language model.
    • Results: Received positive feedback from stakeholders with a 25% boost in user engagement.
    • Technologies Utilized: Google Cloud Storage for storage solutions, Redis for fast data lookup, Azure Text-to-Speech for audio generation, SSML for voice customization, and Java for backend development.
  • Proposed and implemented a new centralized event schema service to resolve schema inconsistencies across VoiceCore services.
    • Facilitated all Kafka events for publishing and subscribing, supporting schema evolution, maintaining consistency, and providing clear documentation and guidelines.
    • Results: Achieved 40% reduction in integration overhead and 25% improvement in debugging time.
    • Technologies Utilized: Apache Kafka for event streaming, Java for backend development, GitLab CI/CD for continuous integration and deployment, and Swagger for API documentation.
  • Designed and developed APIs for establishing SIP connections (IP, FQDN, and Credentials) using Telnyx SDKs, Java, and the Micronaut Framework. Integrated Kafka for event streaming to ensure real-time SIP connections.
    • Results: Conducted feedback analysis, resulting in a documented 20% increase in customer satisfaction.
    • Technologies Utilized: Telnyx SDKs for SIP connections, Java and the Micronaut Framework for API development, Apache Kafka for event streaming, and Junit for testing.
Development Expertise:
  • Optimized utility libraries, leading to a 22% enhancement in code efficiency across VoiceCore's internal services, fostering consistent and standardized code practices while leveraging technologies such as Redis, Log4j, GCP Buckets, Firestore.
  • Enhanced microservices pods by implementing automated backups of thread dumps and heap dumps to GCP buckets in the event of Out-of-Memory (OOM) incidents. This proactive measure resulted in at least a 25% reduction in debugging time.
  • Developed bash scripts to secure transaction logs from pods, reducing on-call debugging time by 3-4 hours weekly for developers.
  • Enhanced data security in production by concealing NPIs, Auths, and tokens in GCP Logs Explorer logs and Kubernetes pods.
  • Boosted test coverage, in multiple microservices using Junit and Jmeter, from 36% to 87%, cutting testing costs by 20%.
  • Initiated and developed a new Inbound call automation bot, collaborating with external teams for E2E testing. Provided knowledge transfer after creating the initial POC for a seamless transition, resulting in reduced debugging time for on-call production.

Software Engineer at Black Knight, Inc., Philadelphia, PA, USA

June 2020 – Jan 2022

  • Worked in the AIVA (Artificial Intelligence Virtual Assistant) team to re-architect and develop APIs for Input & output handler Services.
  • Developed APIs for managing multiple customer environments using AWS services; API Gateway, Lambda, S3, DynamoDB, and SSM.
  • Implemented Microservices to extract data from OCR-generated content, creating multiple data points.
  • Led the development of new, resilient services and orchestrated stacks from the ground up using Python, CloudFormation, and S3.
  • Effectively addressed provisioning and build failures, leading to decreased testing load times and reduced AWS costs.
  • Developed Python scripts using Boto3 to address rare anomalies in transactions caused by code defects or AWS outages.
  • Enhanced microservices tests by 70% by creating acceptance and integration tests using Pytest, Junit, Python Behave, and Java Cucumber.

Research Scholar at Bharati Vidyapeeth's College of Engineering in CSE Department under Dr. Rachna Jain
Jan. 2017 – Sept. 2017

  • Enhance data security in cloud using Steganography
    • Studied about Cloud Service Providers vs Internet Service Providers based on cost, speed, scalability, performance, etc.
    • Reviewed techniques of steganography (Least-Significant-Bits) & digital watermarking (Discrete Fourier Transform) in spatial & frequency domain.
    • In-depth study on Symmetric Key Encryption (DES, AES) & Asymmetric Key Encryption (RSA) major attacks like brute force, frequency analysis.
    • Proposed the model for Image Steganography using LSB, which mapped every bit of data & encryption key in RGB pixels of the image.

  • Medical application using NLP over cloud
    • Knowledge acquisition on NLP system and existing open source libraries (NLTK, Polyglot, Pattern) in the market.
    • Studied about Morphological Processing, Syntax, Semantic and Pragmatic Analysis.
    • Comparative study on 3 different types of clouds (public, private and hybrid) based on reliability, cost, scalability, etc.
    • Proposed a computerized Clinical Decision Support (CDS) System using cloud services to improve the accuracy & the availability.

Consulting & Software Internship at TATA - Computer Management Corp, Delhi, India
May 2016 – Aug. 2016

  • Responsible for full stack API-driven web application, Increased sales of products by 45% & reduced data storage inventory by 38%.
  • Implemented Agile process across the teams, improved customer interaction and feedbacks on sprints.
  • Developed RESTful-APIs using Python with flask framework, with JWT Session Management for user security.
  • Performed ETL on old database, to get new & optimized Data, improved performance w.r.t. to time, by 30% in each query.
  • Interacted with the DB using MongoDB Alchemy (NoSQL), which improved the flexibility & provided Object-Oriented Structure to DB.

Android App Development Trainee at Bharati Vidyapeeth's College of Engineering, Delhi, India
May 2015 – Jul. 2015

  • Developed a Video player using Android studio that will access video files from the storage in List or Grid View.
  • Users can play, organize and use hand gestures to control the flow of the video.
  • Worked in App. UI, deep functionality and Third-Party SDK (like Android Studio).
  • Gained experience in Java and Android Studio.


RosterData Website for Ice Hockey Statistics Inc. Version 2 [Capstone]

Jan. 2020 – Apr. 2020

Enhanced RosterData for Ice Hockey by developing Version 2, which integrates three additional leagues alongside existing ones. The new leagues were scraped from,, and

  • Contributed to the implementation of multiple ice hockey leagues on the main website within an Agile team environment.
  • Developed web scraping scripts using Python and Scrapy Framework to gather statistics from new leagues.
  • Modeled scraped data into JSON format and imported it into PostgreSQL on Amazon RDS.
  • Collaborated on the development of APIs to fetch scraped data from AWS PostgreSQL, integrated with the front-end.
Latent Semantic Analysis Classification and Prediction

Mar. 2020 – Apr. 2020

Trained a machine learning model on sensitive financial encoded documents for classification and prediction.

  • Mapped sensitive financial encoded documents into unique IDs for analysis.
  • Trained and deployed a document classification model based on encoded patterns using Python, pandas, and scikit-learn.
  • Developed Flask RESTful APIs for serving machine learning predictions.
  • Achieved 98% accuracy and 87% confidence on average in model testing.
  • Deployed machine learning APIs on Google Cloud Platform for integration testing.
Diabetes Patient Classifier & Clustering on Meal Data

Aug. 2019 – Nov. 2019

Implemented a machine learning model to classify diabetes patients based on diet and sugar level readings, along with clustering meal data according to carbohydrate intake.

  • Extracted features from raw patient data after preprocessing and cleaning using Python, Pandas, and NumPy.
  • Developed and implemented APIs for dimensionality reduction using Principal Component Analysis (PCA) with Matplotlib and Scikit-Learn.
  • Conducted in-depth analysis using K-fold Cross Validation to select the best classifier and clustering algorithms with Scikit-Learn.
  • Achieved 85% accuracy on patient testing data with an 83% confidence level on new predictions.
Online Visual Learning Portal

Aug. 2019 – Nov. 2019

Designed and developed an interactive Online Visual Learning Portal where students of varying grades engage with mathematical concepts through drag-and-drop functionality, solving questions assigned by their professors.

  • Collaborated within a team of 5 to develop the portal using Agile methodology with Scrum.
  • Implemented design patterns like Facade, Factory, and Iterator to construct RESTful APIs for seamless application functionality.
  • Designed and implemented the backend service in Python using Flask-Framework, incorporating Flask-Login for enhanced user security.
  • Utilized SQL-Alchemy for standardized database interactions, promoting an object-oriented approach over hard SQL queries.
!Xobile Programming Language

Jan. 2019 – May 2019

Developed our own programming language based on java & python, which can handle all basics functions plus object oriented programming, with some unique features.

  • Worked in a team of 4, to develop !Xobile programming language similar to any Object-Oriented Language using Python & Prolog.
  • Designed and developed the Grammar of the language, Tokenization using Python, Syntax Parse Tree & Semantics using Prolog.
  • Developed scripts using Python for automation, which executes all the files and produces the output for the given lines of code.
Hadoop Cluster Implementation and MapReduce API Development

Mar. 2017 – Jun. 2017

Established a Hadoop cluster on a local system using virtual nodes and developed a MapReduce API for YouTube raw data analysis.

  • Designed and implemented a MapReduce application to extract top YouTube video creators for a given week using Python.
  • Processed 300 million YouTube video logs, further subsampled into 10 sets.
  • Created an eight-node Hadoop cluster and automated the process.
  • Conducted a comparison study on multiple Hadoop versions to ensure backward compatibility.

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