Karthik Sridhar / SOFTWARE ENGINEER
MOUNTAIN VIEW, CALIFORNIA · CMU SOFTWARE ENGINEERING

Karthik SridharAI workflows.
Reliable systems.
Useful products.

Backend EngineeringAI AgentsFull-Stack DevelopmentFintech

Software engineer and CMU master’s student working across AI workflows, backend systems and business software. Explore the live applications below, then look inside the implementation: data contracts, failure handling, tests and design tradeoffs.

BUILT TO BE USED

Tools you can actually explore.

Live data. Your own inputs.
No accounts or sign-up forms.

⌘ RepoScopeREPOSITORY INTELLIGENCE
▾ src
 ▤ index.ts
 ▤ router.ts
▾ tests
 ▤ router.test.ts
▾ .github/workflows
ENGINEERING SIGNALS

CI workflows Found

Test files Found

Exact dependencies Inspect →

Interface preview · inspect any public repository in the app
01 / DEVELOPER TOOLING + SUPPLY CHAIN

RepoScope

A public GitHub investigation workspace. Understand a repository’s structure, browse source files, review activity and check resolved npm versions against OSV vulnerability advisories.

  • Server-side GitHub integration with persistent caching
  • Searchable file explorer and source previews
  • Version-aware dependency audit with advisory links
  • Timestamped, downloadable investigation reports
React / TypeScriptCloudflare WorkersD1 / SQLiteGitHub + OSV APIs
≋ SignalDeskINCIDENT INVESTIGATION
EventsImport your logs
Error rateInspect
P95 latencyMeasure
gateway → booking-api → ledger
Import · filter · correlate · export evidence
Interface preview · accepts real CSV, JSON and NDJSON
02 / OBSERVABILITY + DATA WORKFLOWS

SignalDesk

A log investigation workspace for real files. Move from raw events to service-level metrics, a searchable event explorer, trace waterfalls and an exportable incident brief.

  • CSV, JSON and NDJSON import with row validation
  • Service, severity, search and time-window filters
  • P95 latency, error timelines and trace investigation
  • Local processing: imported logs stay in your browser
React / TypeScriptData parsingObservabilitySVG visualization

Independent portfolio applications built with AI-assisted development. Public repositories retain their original ownership; repository content is inspected, not presented as my own code. SignalDesk’s optional sample is clearly labeled as generated data.

BEYOND A RÉSUMÉ

The decisions behind the interface.

Read the engineering notes ↗
01 / DATA INTEGRITY

Don’t guess a version.

RepoScope distinguishes a declared dependency range from an exact lockfile version. Only exact versions go to the advisory service, and every result retains its source and retrieval time.

02 / FAILURE HANDLING

Make partial results honest.

Independent upstream requests can fail independently. Repository reports flag missing sections and truncated trees; the cache can serve a labeled stale snapshot when GitHub is unavailable.

03 / MEASUREMENT

Show the evidence.

SignalDesk exposes the denominator behind an error rate, uses a defined nearest-rank percentile and labels deployment correlations as leads. The public analytics dashboard records real events from launch.

BACKGROUND / EDUCATION

A foundation for building.

GRADUATE STUDIES

MS Software Engineering

Carnegie Mellon University

Aug 2026 – Expected May 2027 · Silicon Valley

CURRENT COURSEWORK
18-652 · Foundations of Software Engineering18-755 · Networks in the Real World18-654 · Software Testing and Operations18-668 · Data Science for Software Engineering
UNDERGRADUATE STUDIES

BE Information Technology

SIES Graduate School of Technology

2019–2023 · Grade: 9.31

Teaching Assistant — Database class
RELEVANT COURSEWORK
Database Management SystemsData Structures & AlgorithmsOperating SystemsComputer NetworksObject-Oriented ProgrammingSoftware Engineering
CAPABILITIES / SKILLS

Engineering across the stack.

Select a focus to explore my toolkit.

Backend & data

Application services and business workflows.

JavaSpring BootPythonPostgreSQLSQLRedisAWSDistributed Systems

AI-agent engineering

Retrieval, tool use, and evaluation.

PythonLangGraphLangChainRAGTool CallingResponse Evaluation

Applications & delivery

From understanding a business to shipping software.

TypeScriptReactRequirements TranslationStakeholder CollaborationTestingEnd-to-End Delivery
EXPERIENCE / SELECTED WORK

Software with a business context.

Professional experience. Clear ownership.
Results grounded in the work.

FOUNDING ENGINEER · 2025–2026

GoldJar

Bringing offline bullion operations online.

Visit product ↗
US$1M+daily trading volume supported by the platform

Start with how the business works.

I worked directly with business owners to translate gold-wholesale operations into application logic, building GoldJar end to end alongside my full-time Jio role.

My contribution
  • Pricing and dealer-booking workflows
  • Order management and administration
  • Customer-facing application features
  • Implementation, testing, and delivery
  • Internal AI agents
Business outcome

The platform now supports over US$1 million in daily gold and commodities trading volume. The business has reached profitability and onboards multiple clients each day.

Trading volume represents transaction value, not revenue.
Discuss this project in an interview +

Walk through a real booking from user action to order state. Explain which business rules you implemented, how pricing was represented, and how you tested changes.

  • Which parts did you personally design and build?
  • How did you handle invalid inputs and changing business requirements?
  • What would you improve for retries, auditability, and concurrent requests?

These are discussion prompts, not claims that a specific architecture was used.

SOFTWARE ENGINEER · JIO MATRIX

Incentive
management

An internal application for Reliance Retail.

3 monthsend-to-end delivery

Turning stakeholder requirements into workflows.

In the Jio Matrix team, I worked with stakeholders to translate incentive-management requirements into an internal application and owned delivery end to end.

Scope

Requirements translation, application implementation, testing, and delivery of the incentive-management workflow.

Reported impact

Reduced manual effort and improved productivity by 90% for the workflow.

The figure describes workflow productivity, not a company-wide improvement.
Discuss this project in an interview +

Prepare a sanitized example of an incentive rule, how you clarified it with stakeholders, and how you validated the application against the original process.

  • What was in scope for the three-month delivery?
  • How was the 90% productivity improvement measured?
  • Which requirement changed, and how did you respond?
SOFTWARE ENGINEER · JIO PLATFORMS

JioMeet &
JioEvents

Communication services and AI-agent workflows.

Built real-time features and AI assistants using Python, LangGraph, and LangChain. Worked on tool calling, retrieval, response evaluation, and system performance.

Helped scale online meetings from 50 to 5,000 participants and reduce infrastructure costs by 25%.

PythonJava / Spring BootRAGRedisAWS
RESEARCH / PUBLICATIONS

From experiments to published work.

SPRINGER · 2025

Identifying duplicate questions

Empirical Comparison of Machine Learning Algorithms to Identify Duplicate Questions on Various Social Media Forums

Karthik Sridhar & Pranita Mahajan · CCIS 2440 · 22 May 2025

Compared a random baseline, Logistic Regression, Linear SVM, and XGBoost for duplicate-question identification using Matthews correlation coefficient.

Machine LearningText ClassificationXGBoostEvaluation

Read publication ↗

IEEE · ICOSEC 2023

Street-sign recognition

Real-Time Detection and Classification of Street Signs Using Deep Learning with Voice Alert system

Samundiswary S, Karthik Sridhar, Mehul Aswar & Simran Kaur Shembe · IEEE Xplore, 16 October 2023

A LeNet convolutional neural network for German street-sign classification, paired with text-to-speech alerts.

Computer VisionDeep LearningCNN / LeNetText-to-Speech

Read publication ↗

BUILD IN THE OPEN

A transparent view of reach.

Explore live analytics ↗

Visit the dashboard for recorded traffic.

Country-level reach, daily visits, device mix, project launches and CV opens—drawn from actual aggregate events. No fabricated counters. No IP addresses or uploaded log content stored in analytics.

ABOUT / HOW I WORK

Build. Learn. Take ownership.

I enjoy working where engineering meets business operations: understanding a workflow, finding the rules that matter, and turning them into usable software.

I’m exploring 2027 new-grad opportunities and internships in backend software engineering and AI-agent engineering.

Get in touch ↗

Carnegie Mellon University

MS Software Engineering · Silicon Valley
Expected May 2027

  • Foundations of Software Engineering
  • Networks in the Real World
  • Software Testing and Operations
  • Data Science for Software Engineering

SIES Graduate School of Technology

BE Information Technology · 2019–2023
Grade: 9.31 · Teaching Assistant, Database class

LET’S BUILD SOMETHING USEFUL.

Have a problem
worth engineering?

karthiksridhar2026@gmail.com ↗