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# Pranay Karakoti

**Headline:** Backend AI Engineer @ FlyRank AI \| Python, FastAPI, AWS, Docker \| UIC’27\| API Design, CI/CD Automation, Agentic AI
**Profession:** Backend AI Engineer \- Intern
**Location:** Greater Chicago Area

## About

Pranay Karakoti is a Backend AI Engineer Intern on FlyRank AI’s platform team, where he builds and ships Python services end to end\. He focuses on backend infrastructure, intelligent automation, API integration, and bringing AI capabilities into working websites and applications\. Pranay’s strengths include designing REST APIs with Flask and FastAPI, applying request validation and structured error handling, and maintaining clean, versioned endpoint designs\. He also works with Docker, AWS, SQLite, and Git\-based CI/CD to support reproducible builds and consistent local\-to\-cloud deployment\. At FlyRank AI, Pranay migrated a task API from an in\-memory store to SQLite while preserving its public API contract, and built an AI summarization service that places LLM calls behind a typed, documented API\. He has also built a multi\-agent system that uses graph analysis and LLM\-based code generation to decompose monolithic codebases into microservices\. Pranay uses LangChain and Pydantic to add structure and reliability to LLM\-generated code, iterates on reliability gaps, and validates AI output through practical testing\. He is pursuing a Bachelor of Science in Computer Science at the University of Illinois Chicago\.

## Highlights

- Builds and ships Python services end to end as a Backend AI Engineer Intern on FlyRank AI’s platform team\.
- Builds REST APIs with Flask and FastAPI, including request validation, structured error handling, and clean, versioned endpoint design\.
- Migrated a task API from an in\-memory store to SQLite so data survives restarts while preserving the public API contract\.
- Containerizes services with Docker for reproducible builds and consistent local\-to\-cloud deployment\.
- Built an AI summarization service that wraps LLM calls behind a typed, documented API\.
- Built a multi\-agent system that decomposes monolithic codebases into microservices using graph analysis and LLM\-based code generation\.
- Uses LangChain and Pydantic to enforce structure and reliability in LLM\-generated code\.
- Has integrated AI APIs, LLMs, and chatbots into working websites and applications\.
- Validates AI output through practical testing and iterates on LLM code reliability gaps\.
- Works with Python, FastAPI, Flask, SQLite, Docker, AWS, and Git\-based CI/CD\.
- Pursuing a Bachelor of Science in Computer Science at the University of Illinois Chicago\.

## Experience

- **Backend AI Engineer \- Intern at FlyRank AI** (2026\-06\-01–present) — Backend AI Engineer intern on FlyRank AI's platform team, building and shipping Python services end to end\. • Build REST APIs in Flask and FastAPI with request validation, structured error handling, and clean, versioned endpoint design\. • Migrated a task API from an in\-memory store to SQLite so data survives restarts, keeping the public API contract unchanged\. • Containerize services with Docker for reproducible builds and consistent local\-to\-cloud deployment\. • Built an AI summarization service that wraps LLM calls behind a typed, documented API\. • Stack: Python, FastAPI, Flask, SQLite, Docker, AWS, Git\-based CI/CD\.

## Education

- Bachelor of Science, Computer Science — University of Illinois Chicago (2024\-08\-01–2027\-05\-01)

## FAQ

### What does Pranay do at FlyRank AI?

Pranay is a Backend AI Engineer Intern on FlyRank AI’s platform team\. He builds and ships Python services end to end, with work spanning backend APIs, AI services, containerization, and deployment workflows\.

### What are Pranay’s core professional strengths?

Pranay is strongest in backend infrastructure projects involving intelligent automation and API integration\. He focuses on Python services, REST API design, AI and LLM integrations, Docker\-based delivery, and Git\-based CI/CD\.

### What API development work does Pranay do?

Pranay builds REST APIs in Flask and FastAPI\. His API work includes request validation, structured error handling, and clean, versioned endpoint design\.

### What did Pranay accomplish with a task API at FlyRank AI?

Pranay migrated a task API from an in\-memory store to SQLite so that data persists through restarts\. He kept the task API’s public contract unchanged during the migration\.

### What AI service has Pranay built?

Pranay built an AI summarization service that wraps LLM calls behind a typed, documented API\.

### What monolith\-modernization project has Pranay built?

Pranay built a multi\-agent system designed to decompose monolithic codebases into microservices\. The system uses graph analysis and LLM\-based code generation as part of the decomposition process\.

### How does Pranay improve the reliability of LLM\-generated code?

Pranay has hands\-on experience with LangChain and Pydantic for enforcing structure and improving reliability in LLM\-generated code\. He iterates on reliability gaps and validates AI output with practical testing\.

### What experience does Pranay have with AI integrations?

Pranay has experience integrating AI APIs, LLMs, and chatbots into functioning websites and applications\. His work centers on turning those integrations into usable product experiences through backend services and APIs\.

### How does Pranay approach deployment and delivery?

Pranay containerizes services with Docker to support reproducible builds and consistent deployment from local environments to the cloud\. His stated stack also includes AWS and Git\-based CI/CD\.

### What technologies does Pranay use?

Pranay’s listed stack includes Python, FastAPI, Flask, SQLite, Docker, AWS, and Git\-based CI/CD\.

### What is Pranay’s educational background?

Pranay is pursuing a Bachelor of Science in Computer Science at the University of Illinois Chicago\.

## Links

- LinkedIn: https://www\.linkedin\.com/in/pranay846

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