ian
computer science student @ fiu
i'm currently interning at amazon, building llm-powered diagnostic systems that ties together aws bedrock with real-time data from internal services for faster debugging and issue resolution
previously at google (summer 2024 & 2025), where i helped modernize the play store's backend infra by modularizing services, redesigning core logic, and driving feature rollouts across high-traffic systems
in fall 2024, worked as a ta at fiu cis 3590 mentoring 45 students contributing to open-source projects and helping them polish their resumes and linkedins
i like working at the intersection of infrastructure, ai, and complex backend systems — building things that scale and solve real problems
Ian C. Borges
Education
- GPA: 3.97
- Relevant coursework: Data Structures & Algorithms, Systems Programming in C, Algorithms & System Design, Intro to Software Engineering with GenAI, Intro to Machine Learning, Statistics for Engineers
- Honors & Awards: Bright Future Florida Academic Scholar, FIU Gold and Blue, National Hispanic Merit Award
- Google Tech Exchange Scholar — completed courses taught by Google software engineers
Technical Skills
- Languages: Java, C/C++, Python, SQL, C#, TypeScript, JavaScript, HTML/CSS
- Frameworks: Spring, Flask, React, Node.js, gRPC, Protobuf, JUnit, Mockito, REST
- Technologies: Git, GCP (BigQuery, Spanner), AWS (Bedrock, Kendra), PostgreSQL
Experience
- Built an LLM‑driven diagnostic framework using Amazon Bedrock to centralize documentation and architectural data, enabling AI‑assisted investigation and faster issue resolution.
- Created an ingestion pipeline that pulls packages, docs and wikis into S3, indexes with Amazon Kendra, and exposes via a Bedrock knowledge base for contextual retrieval.
- Developed an MCP agent layer to securely invoke AWS Lambda and fetch real‑time ticket, deployment, and log data for LLMs during reasoning.
- Integrated with ticket resolution workflows and established a scalable foundation for automated diagnostics across teams.
- Engineered backend infrastructure for Google Play to enable dynamic enforcement of platform limits; improved scalability and configurability in high‑throughput systems (Java, SQL, Protobuf).
- Drove a safe rollout with staged deployments gated by experiment flags; used integration and manual testing to catch regressions and ensure correctness.
- Redesigned business logic, removing deprecated Protobuf schemas and restructuring code for flexibility and backward compatibility.
- Authored a technical design doc that scoped requirements, evaluated tradeoffs, and guided launch; reviewed by senior engineers.
- Developed promotion validation infrastructure for Google Play’s backend APIs (Java, Protoconfig, Guice) supporting 45+ use cases.
- Launched the infrastructure and monitored 5+ KPIs with real‑time streaming tools; swiftly resolved issues.
- Achieved ~90% unit test coverage; added integration and end‑to‑end tests to ensure reliability.
- Assessed adoption of a new Protocol Buffer framework; explored capabilities and presented findings to the team.
Projects
- Built a full‑stack app to estimate carbon emissions from daily routes; suggested eco‑friendly alternatives via Google Maps API.
- Implemented session‑based auth with secure tokens; managed data with H2/JPA; secured REST endpoints with access checks and locking.
- Built a full‑stack Streamlit app delivering personalized fitness and nutrition recommendations via Vertex AI models.
- Managed data and query optimization with BigQuery/SQL; added unit/integration tests; automated CI/CD with Docker and GitHub Actions.