Aditya Bharadwaj
Email: adityabharadwaj198@gmail.com
Phone: +919113955012
Location: Bengaluru, Karnataka, India
Work Experience
Software Engineer 2
Marqo.ai | Melbourne, Victoria, Australia | September 2024 - June 2025
- Part of Marqo’s open source team working on the core product
- Led design & implementation of partial updates, enabling customers to update document fields like number of sales, reviews etc. in real time without having to vectorise a document. The feature was critical for onboarding a customer who later signed a multi-million dollar contract. Tech used: Python, Vespa DB, Docker
- Led design & implementation of a testing pipeline that run backwards compatibility and rollback tests against the to-be released Marqo docker image & previously released Marqo images. Saved 2.5+ days worth of Senior SWE time per two week sprint. Tech used: Python, Docker, GitHub actions
Software Development Engineer 2
Amazon | Bangalore, Karnataka, India | October 2022 - August 2024
- Reduced the number of customer drop-offs by improving the Payment Selection Page to UPI MPIN page load latency by 4 seconds through prefetching assets and parallelizing workflows. Tech used: Scala, Java, Javascript, AWS DynamoDB, EC2, SQS, SNS
- Led the adoption of 3DSecure2.0 protocol for card transactions, aligning with bank guidelines. Implemented new APIs and streamlined the preauthentication process, enhancing security for the 44% of transactions attributed to card payments. Tech used: Java, AWS DynamoDB, Step Functions, SQS
- Improved security of a new payments selection page that serves 41% of traffic by designing and implementing robust authentication and authorization mechanisms. Also handled security audits for the same, addressing risks such as cross-site scripting (XSS), cross-site request forgery (CSRF) etc. Tech used: Java
Software Development Engineer
Amazon | Bangalore, Karnataka, India | June 2020 - September 2022
- Enabled processing of nearly 11,000 daily recurring payment transactions through UPI Emandate on Amazon by building platform-level functionality. This solution caters to both Amazon Pay UPI customers and external third-party UPI customers, reinforcing the seamless execution of financial transactions on the platform. Tech Used: Java, DynamoDB, Step Functions, SQS, SNS
- Designed a microservice that enriches payments data and displays it on transaction history which serves 2M page hits per day. Created it using the AWS ECS Fargate infrastructure with Amazon’s internal RPC framework from scratch. Handled the complete infrastructure, authentication, authorization. Setup logs, metrics and alarms all while maintaining high software engineering standards. Tech used: Java, ECS Fargate, Lambda, DynamoDB, SQS
- Improved latency of a payment processing API used by high value business customers like AWS & Amazon Ads by 5 seconds. Tech used: Java
- Reduced customer contacts by ~121k by contributing to various UI experiments on the Your Transactions page of Amazon Pay, enriching data from various sources at the backend. Tech used: Java, Javascript
- Mentored interns as well as new joinees and served as their onboarding buddy
- Consistently handled on-call load for a ‘Tier-1’ service
Research Intern
Indian Institute of Science | Bangalore, Karnataka, India | January 2020 - May 2020
- Reinforcement Learning in non-stationary environments. Worked on markov chains, MDPs, Baum Welch algorithm, Partially observable MDPs, Point Based Value Iteration
- Used various ML techniques to accurately predict Band-Gap/Band-Alignment values for semiconductors
Education
Bachelor of Technology in Computer Science
Manipal Institute of Technology | Manipal, Karnataka, India | August 2016 - June 2020
GPA: 8.2
Skills
Languages
Java, Python, C++, JavaScript, Scala
AWS
EC2, Step Functions, DynamoDB, Lambda, ECS Fargate, SQS, SNS, VPC, Route 53
AI/ML
Vespa (Vector DB), LLMs
Misc
LangChain, Docker, MySQL, System design, Event driven architecture
Awards
Amazon Pay India Hackathon
Amazon India Payments Experience Tech Org | September 2023
Built a RAG application when RAG was not popular, it was an application that lets you talk to internal Amazon wikis. Used Langchain, Pinecone, Python and React