LEVI DAWIT

UVA CS • Software Engineer

Hi, I'm Levi Dawit

I build practical, reliable software—shipping fast without breaking trust. Experience in serverless AWS architecture, AI/ML pipelines, data engineering, and cloud-native systems.

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Levi

About

I'm Levi Dawit, a software engineer driven by curiosity, creativity, and a love for building things that make an impact. I specialize in designing and developing scalable, user-focused software — from cloud-native backend systems to polished mobile and web applications.

I've built projects that blend AI, cloud architecture, and real-world utility — like ScaleScan, an iOS app that automates data entry from weight tickets using image processing, and Social Sage AI, a generative-AI pipeline that crafts social media content through AWS Bedrock and serverless orchestration. I enjoy the challenge of translating complex ideas into reliable, elegant systems that people can actually use.

Most recently, I worked as a Solutions Architect Intern at Amazon Web Services, where I developed end-to-end serverless data pipelines and integrated LLM-powered applications using Bedrock, Lambda, and Step Functions. My work there deepened my interest in distributed systems, observability, and how AI can augment human workflows.

Beyond code, I love learning new tools, picking up side projects, and even new skills — like golf — because I believe that growth comes from staying curious. Whether it's building an app, designing cloud infrastructure, or exploring a new API, I approach every challenge with the same goal: to learn something new and make something meaningful.

Skills

Java C/C++ Python TypeScript Swift SQL React React Native Node FastAPI Docker GitHub

Languages

Java Java C++ C/C++ Python Python TypeScript TypeScript Swift Swift SQL SQL

Frameworks & Tools

React React React Native React Native Node Node FastAPI FastAPI Docker Docker GitHub GitHub

Certifications

AWS Certified Cloud Practitioner AWS Certified Solutions Architect – Associate

Education

UVA

University of Virginia

B.S. Computer Science • 2022–2026

Relevant courses: Data Structures, Computer Systems, Software Engineering, Cybersecurity, Machine Learning.

Woodberry Forest School

2019–2022

Graduated with honors. Varsity football and track.

Experience

AWS

  1. Solutions Architect Intern — Amazon Web Services (AWS)

    May 2025 – Aug 2025 • Austin, TX

    • Built and demoed a full-stack AI data pipeline on a serverless AWS architecture (Lambda, Step Functions, DynamoDB) to transform raw scraped data into LLM-generated insights, demonstrating end-to-end automation from ingestion to inference.
    • Designed and deployed real-time ETL workflows using AWS SAM and CDK, optimizing performance for unstructured data and reducing end-to-end latency by over 80%.
    • Integrated foundation models via Amazon Bedrock APIs to enable scalable content generation and text summarization, showcasing AI-driven workflows within cloud-native systems.
    • Collaborated with cross-functional teams and presented architecture designs to technical and client stakeholders, aligning AI/ML solutions with business objectives and demonstrating tradeoffs between latency, scalability, and cost.

  2. Interstate Moving — Software Engineering Intern

    May 2024 – Aug 2024 • Springfield, VA

    • Designed and launched an iOS app (Swift, REST) for scanning/transmitting weight tickets, cutting manual data entry by 30%.
    • Implemented secure, real-time data transmission between drivers and dispatch.
    • Gathered requirements and iterated through testing for high adoption and fewer errors.

Projects

ScaleScan

ScaleScan

  • iOS app that scans weight tickets and sends structured data to dispatch.
  • Reduced manual entry time by 30% with OCR + async processing.
  • Built with React Native, REST API, and image processing.
Course Review

Course Review Application

  • Web app for students to review courses and instructors.
  • Helps improve selection decisions and community feedback loops.
  • Developed using Java and SQLite.
Social Sage AI

Social Sage AI

  • Generative AI pipeline for social media captions/posts using Amazon Bedrock + LLMs.
  • Fully serverless backend with Lambda, Step Functions, API Gateway, DynamoDB.
  • React frontend for input + near real-time AI results.
  • Emphasized scalability, low-latency inference, and fault-tolerant cloud design.
  • TypeScript, Node.js, AWS Bedrock, Step Functions, DynamoDB, React (May 2025 – Present).

Contact

University of Virginia, Charlottesville, VA

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