🏢 Software Engineering Experience

Role: Systems and Infra SWE PhD Intern
Location: Seattle, WA, USA
Duration: May 2025 - Aug 2025
Team: Data Flows (under Privacy Org.)

🔹 Work Highlights:

Problem: Probes, a runtime analysis tool at Meta can detect if data from a source asset reaches a sink asset, but it does not explain why or how the data flows between them. To determine the cause, human reviewers must manually inspect hundreds of execution evidences per source-sink pair. Each evidence contains detailed read and write stack traces with long chains of function calls, making this process time-consuming and error-prone. Reviewing a single stack trace evidence manually by an expert can take ~20 minutes.

• Designed and implemented an AI agent that analyzes stack traces and function definitions to identify declassification or data flows between source-sink pairs in under 2 minutes per evidence.
• Built an iterative reasoning process where the agent processes stack trace chunks step-by-step first along the read path, then along the write path.
• Enabled the agent to:
  • Pinpoint the exact code location of declassification, or
  • Provide justification (with supporting code) when the data flow is preserved.
  • Explicitly handle class-level variables storing source data.
• Evaluated performance against static analysis results and admin-approved ground truth:
  • ~70% precision/recall at the individual evidence level.
  • ~94% accuracy for identifying declassification at the source-sink pair level.
  • ~78% accuracy for detecting complete source-to-sink data flows.
• Integrated the agent into the UI with a direct link to its full reasoning output.
• Developed monitoring alerts for performance and cost measurement.
• Developed Unit Tests to ensure new changes in the agent does not cause impact the main functionalities.
• Collaborated with cross-functional teams to extend their multi-agent AI framework for this use case.
• Designed and implemented a lineage graph visualization using a fast graph traversal API, and contributed new features back to the traversal API.
• Tech stack - HACK, Python, React, SQL.
• Experiemented with models: LLAMA, CLAUDE, GEMINI.
• Tools - Mercurial (VCS)

Role: Software Engineering Internship
Location: NYC, NY, USA
Duration: May 2022 - Aug 2022
Team: Privacy Approval Monitor (under Messenger Org.)

🔹 Work Highlights:

Problem: To be able to visualize data flow from Messenger features to sensitive tables before production release.

• Developed a UI tool that detects sensitive database access in code blocks, leveraged by software team leads before code production release.
• Developed another UI tool to show data flows within various privacy assets across Meta (e.g., data flow from mailbox API to stored procedure to database).
• Worked with cross functional teams to upload target dataset in Meta’s lineage system.
• Tech stack - React, GraphQL, HACK, PostgreSQL, Python, Dataswarm pipeline.
• Tools - Mercurial (VCS)

Role: Software Enginer
Location: Pune, Maharashtra, India
Duration: July 2019 - August 2021
Team: Global Credit Module (GCM) (under Wealth and Personal Banking (WPB))

🔹 Work Highlights:

• Worked as a full-stack developer on a product that is primarily used by relationship managers.
• Developed features such as automatic email notifications for credit limit approvals and rejections, SMS alerts for credit margin status, Jasper reports, rule assignments for securities received from batch process etc.
• Monitored production batch.
• Performed code management during production release.
• Tech stack - Java, DB2, Sprint Batch
• Tools - GitHub (VCS), JIRA (Task management in Agile SDLC), Jenkins (Deployment), G3 (Deployment)