About Me
I am Shubham Jindal, currently working as Senior Software Engineer at TikTok in Global Payments Team. I have over 6+ years of experience in the tech industry. At TikTok, I work on building highly available and resilient payment systems where we process more than $50 Million transactions everyday on TikTok Shop.
Before TikTok, I spent 3 years at Flipkart (a Walmart subsidiary), where I led a team of software engineer in Search Spyder data team. I also worked in Retail where I contributed in build exchange micro-services.
I hold a Bachelor’s degree in Computer Science & Engineering from the prestigious Indian Institute of Technology (IIT) and a Master’s degree in Computer Science from Stony Brook University.
Experience
Joined as Senior Software Engineer and leading TikTok Shop Payments for TikTok's Global Payment Systems.
- Led a team of 5 engineers at TikTok USDS Global Payments to design, develop, and maintain core payment services for payout, refund, and pay-in use cases. Developed features to process payments through multiple payment providers, including PayPal, Braintree, Stripe, Adyen, Affirm, and Hyperwallet for Wallet and Card Payments. Resolved 30+ critical bugs in Q1 2024, reducing refund customer complaints by 95%.
- Worked in launching Payments for GauthMath, TikTok Shop and Capcut in USA by making sure all payment systems are in place before the launching. Collobarated with Testing teams to test payment scenarios.
- Built a Diff Tool to track and resolve multiregion data center middleware configuration discrepancies (RDS, TCC, TCE, Neptune). The tool was adopted in multiple teams, including AML, Risk, and Hive, improving operational efficiency.
- Developed a Compliance Tool that serves as a unified platform to manage evidence in various compliance projects in Global Payments. Features include evidence storage and retrieval, automated notifications, UI-driven group creation, escalations, and complete lifecycle management from submission to approval.
- Automated multiple monitoring and analytics processes, including merchant traffic tracking, capture/auto-capture success rate validations and proactive refund resolution. Redesigned the RichDog alerting system, significantly reducing false positives and system noise.
- Provided 24/7 on-call support for Global Payments across EU, TTP, and RoW regions. Optimized alarm configurations and improved SLA for incident resolution through proactive monitoring and rapid response strategies.
- Technologies: GoLang, Python, MySQL, Redis (distributed locks), RPC, Microservices, SOA, Distributed Systems, High-Level & System Design, Concurrency Management
Joined as Software Development Engineer & led Search Spyder Data team and owned exchange services in Retail team.
- I designed and implemented new business features for exchange and trade-in micro-services backed by relational data store. I have experience in complete SDLC process from design to oncall maintainance.
- Developed micro batched pipelines to create materialized views to capture the user journey stitching the user and server events across time windows for ranking, semantics and autosuggest components consumption for clickstream analysis.
- Re-tuned spark pipelines along with appropriate GC settings for BBD user traffic growth of 10x .
- Developed reporting dashboards to allow business to get view of search ranking across multiple dimensions like city, speed, price etc using druid + spark stack.
- Technologies Used: Java, Dropwizard, MySQL, Guice, HDFS, Apache Airflow, Apache Spark, Scala, Python, Apache Kafka, Apache Superset, Apache Druid.
Joined as Software Development Engineer in Infrastructure as a Service (IaaS) team.
- Developed Hardware Resource Monitoring Platform to monitor, analyze and proactively report (near real-time) the physical/virtual resource failures with an aim to improve Resource Availability and reduce Operational Expenses by 30%.
- Technologies Used: Python, Redis, Flask, CSS, Spark, Object Oriented Programming, Design Patterns (Chain of Responsibilities)
Projects
This will revolunize the stock trading and investment in USA.
I started this project in 2024 Jan and currently the app is in development. This app will allow people to follow their favourite stock influencers, get latest news about the stocks and stock analysis to make good trading and investment decisions.
Education
Stony Brook University, New York
Masters of Science in Computer Science
2021 - 2022
Stony Brook University
🎓Graduated from SBU in 2022 with GPA of 3.77/4.00. During this degree I took courses like Distributed System, Data Science, Probability, Computational Biology etc.
Indian Institute of Technology, Guwahati
Bachelor's of Technology in Computer Science and Engineering
2015 - 2019
Indian Institute of Technology Guwahati
🎓Completed my undergraduate in 2019 with CGPA of 8.21/10.00. During this degree I took many important course to laid the foundation of my Software Engineer career. My coursework included: Data Structure, Discrete Mathematics, Algorithms, Theory of Computation, Artificial Intelligence, Computer Vision in Machine Learning, Databases, Computer Networking, Compilers, Software Engineering, Operating System, Natural Language Processing
Publications
Introduction to Digital Payments in the United States of America
Publishing Date: Aug 2025
Publisher: International Journal of P2P Network Trends and Technology (IJPTT)
Abstract:
Digital Payments in the USA are revolutionizing, and to be ahead in the growing sector, it is essential to
understand how digital payments in the USA work, which is significantly different from how some other countries,
like India, process payments. At the core of USA digital payments is the Authorization and Capture, which is
not followed in countries like India. This article will summarize core digital payment concepts and provide an
overview of how digital payments work in the USA. We will review Payin, Payout, Refund, Authorization Reversal,
Void, Chargebacks, and Reversal Adjustments. The article will then explain payment flows in offline and online
environments. It will then introduce advancements in online payments, which use merchant-initiated captures
along with partial voids, partial Capture, and partial refunds. This article will focus only on credit and
debit card transactions. In the future, the article will discuss 1) wallet-based transactions such as Apple
Pay, Google Pay, Venmo Card, 2) Account-to-Account transfers or p2p transfers such as Zelle, Venmo Wallet,
3) Settlement, Payout, Chargebacks & Reconciliation in more detail.
Card Payments Refunds, and Chargebacks in United States of America
Publishing Date: Aug 2025
Publisher: International Journal of P2P Network Trends and Technology (IJPTT)
Abstract:
Card payments in the US are secure because of the Authorization and Capture model, but often there is a
scope of fraudulent transactions, which leads to disputes being raised by the customer with their bank. Also,
customers usually want to return the services or products bought at a merchant due to several reasons, such as
customer dissatisfaction with the product or service, poor quality products, or better alternative options.
Now, for the Payment Service Providers, Merchants, and Technical Service Providers, it is essential to support
both refunds and chargeback processing while protecting merchants from fraudulent chargebacks raised by scam
customers. The article will discuss refunds and the chargeback process in detail. Then the article will
discuss the reconciliation problem, which arises due to the asynchronous nature of refunds and chargebacks,
which also affects payouts, and provide a solution to reconcile the transactions and solve payout problems.
Ensuring Configuration Consistency Across Multi-Regional Data Centers
Publishing Date: February 2025
Publisher: International Research Journal of Modernization in Engineering Technology and Science (IRJMETS)
Abstract:
Today nearly every big company operates several data centers spread across the world. Each of these data
centers hosts a variety of infrastructure services like MySQL, Redis, Hive, Message Queue etc. Now for any
company it’s very important to write the same code for all regions for scalability and following the DRY (Don’t
repeat yourself) aspect of system design. But the people who are designing and writing these codes are spread
across multiple regions and due to that sometimes they are not aligned on every system configs. Sometimes
even within the same region software engineers are not aligned properly on these system configs as to what
system configs to keep for that region. Because of that, data center system configs start differing across multiple
regions. Now it is very important to make sure these configurations are the same across all regions because it
can lead to a major critical issues in your team. In this paper, we will first introduce what the problem is, then
we will talk about existing solutions and then we will talk about proposed solutions and how it tackles all the
problems listed in the introduction section.
📄 Read the Original Article
📄 Read the Dzone Article
Monitoring Server Health in Private Cloud Data Centers: A Scalable Approach
Publishing Date: March 2025
Publisher: International Journal of Computer Trends and Technology (IJCTT)
Abstract:
With the increasing costs of public cloud services such as AWS, Azure, and GCP, many companies opt to establish
their private cloud infrastructure. This transition necessitates the development of an adequate Infrastructure
as a Service (IaaS) team to manage and maintain the data center. A key challenge in this domain is monitoring the
health of the bare metals (also called servers) to ensure high availability and reliability. This paper presents
a comprehensive approach to bare metal health monitoring in private data centers. We will discuss the problem
statement literature review, outline an industry-standard solution, propose a high-level system design to ensure
real-time monitoring, fault detection, and automated remediation, and provide experimental results to show how
our approach is better than existing industry solutions.
📄 Read the Original Article
📄 Read the Dzone Article
Understanding N-Gram Language Models and Perplexity
Publishing Date: July 2025
Publisher: Dzone
Abstract:
Language models are designed to predict what words are likely to come next in a sequence, assigning
probabilities to each possible continuation. In this article, we explore how an N-gram language model works,
how it assigns probabilities to sentences and sequences of words, and then examine how well this model performs.
By understanding and evaluating this approach, we gain insight into how language models handle the complexity of
human language.
Awards & Recognitions
Recognized for my outstanding contribution in academics and industry in the field of computer science, software engineering, payment systems and e-commerce.
One India Media Article
Media Article: One India Shubham Jindal
Institute of Electrical and Electronics Engineers (IEEE)
Award: IEEE Senior Member
Awarded: Mar 2025
Institution: IEEE
Society Acadamic and Scientific Society
Award: Eminent Fellow Member (SEFM)
Awarded: Feb 2025
Institution: SAS Society
Soft Computing Research Society
Award: Fellow
Awarded: Feb 2025
Institution: SCRS
International Organization for Academic and Scientific Development (IOASD)
Award: Royal Fellow
Awarded: Mar 2025
Institution: IOASD