Software Engineer · Chicago, IL

Angelo Francis Landiza

I'm a Software Engineer Intern at Morningstar, where I build full-stack RAG platforms and auto-scaling AWS infrastructure for LLM systems used by thousands of people across the globe.

I study Data Science with a Computer Science concentration at the University of Illinois Chicago — and I've been shipping software since my FRC robotics days, from reinforcement-learning robots to production document-extraction pipelines.

Get in touchGitHubLinkedIn
01

Experience

Mar 2026 — Present

Software Engineer Intern · Morningstar

  • Architected auto-scaling AWS infrastructure (CDK, Fargate, ALB) for a full-stack RAG chatbot, with DynamoDB powering real-time user sessions and low-latency LLM context retrieval.
  • Ship UI features and REST APIs for Illume 2.0, a modular RAG document-extraction platform serving 2,000+ non-technical users across 5 global offices.
  • Cut data-collection turnaround from a ~5-week manual JSON build-and-test cycle to under a minute with UI-driven pipeline configuration, across 1,000+ financial documents per workflow.
  • Co-developed a proposed investment-quality metric and built its prototype — presented to the CEO, CTO, and senior leadership, now in company-wide research for implementation.
  • Engineered the core logic of a regression-testing suite (CDK + SQS) that batch-queues pipeline runs and computes recall and F1 across variants to drive improvements.
  • Retained for a fall-term extension, shipping platform features alongside a full course load.
PythonTypeScriptAWS CDKDynamoDBECS FargateRAG

Jun 2025 — Jul 2025

Lead Summer Robotics Programming Intern · CPS Office of Computer Science

  • Directed a high-school robotics internship, assigning 17 students to projects optimizing FRC and FTC robot performance.
  • Developed curriculum covering robotics programming, computer vision, and autonomous navigation.
JavaPythonOpenCVWPILib

Jun 2023 — Jul 2024

Summer Robotics Programming Intern · CPS Office of Computer Science

  • Built Java software with the WPILib framework for an autonomous swerve-drive FRC robot.
  • Implemented a random maze generator and applied the A* algorithm to find optimal solutions.
  • Constructed a neural network from scratch in Python.
JavaWPILibPython
02

Projects

Revenue Segment Extraction Platform

2026

Retrieval-augmented extraction system for annual-report and 10-K PDFs, built for Fitch in partnership with three finance students and presented to company representatives.

  • Parses PDFs deterministically, ranks revenue-relevant pages, and sends structured context to an LLM.
  • Validates every extracted row against strict Pydantic schemas behind an approval-gated analyst review flow.
  • Scales horizontally via ECS Fargate task parallelism, with CSV, XLSX, and audit-JSON export.
PythonLLM · RAGPydanticStreamlitECS Fargate

Fully Autonomous FRC Robot

2022 — 2024

Reinforcement-learning system for autonomous robot navigation on a competition swerve-drive robot.

  • Trained a PyTorch RL agent that achieved a sub-2-second average game-piece intake.
  • Engineered a custom OpenAI Gymnasium environment simulating robot dynamics and sensor data, with MuJoCo physics and PPO training.
PyTorchGymnasiumMuJoCoReinforcement Learning

T.A.U.I — Train & Uber Integration

2023

Submission to Uber's 2023 Global Hackathon: a web app that plans multimodal routes by pairing train lines with Uber rides.

  • Finds the most convenient stations for origin and destination, then plans the route with the Google Maps API.
  • Generates pre-filled Uber deep links for the first- and last-mile legs — no manual destination entry.
PythonFlaskGoogle Maps APIJavaScript

Retail Arbitrage Scraper

2025

Locally-run, API-key-free tool that finds profitable retail arbitrage opportunities across major retailers.

  • Scrapes clearance listings from Walmart, Target, and Walgreens with Playwright browser automation.
  • Matches items against Amazon pricing with price-aware heuristics, then scores ROI with rule-based buy/review/avoid recommendations.
Node.jsExpressPlaywrightSQLite

More robotics & experiments

AutoPID

Python

Automated PID-tuning lab comparing genetic algorithms, reinforcement learning, and heuristic methods against simulated motors.

FTCYOLOV8

Python

YOLOv8 object-detection training pipeline for FTC game elements, exported to TFLite and ONNX for on-robot inference.

LIDARswerveRL

Python

LIDAR-driven swerve-drive reinforcement-learning experiments, including multi-agent training environments.

4787 SwerveBase

Java

Competition swerve drivetrain codebase for FRC Team 4787 Axiom, built on WPILib.

03

Skills

Languages

PythonTypeScriptJavaC/C++C#Lua

Frameworks & Libraries

AWS CDKPyTorchTensorFlowOpenCVWPILibReactNext.js

Cloud & Infrastructure

AWSDynamoDBS3SQSECSECRALB

Tools

GitJiraBitbucketHarnessPostman

Architectures & Methods

REST APIsRAGAgile (Scrum)
04

Education & Leadership

Expected May 2028

University of Illinois Chicago

B.S. in Data Science, Computer Science concentration

2022 — 2025

Team Lead & Mentor · High School FRC Programming Team

  • Mentored 12 programmers on project protocols and best practices, managing code contributions through Git and in-person reviews.
  • Developed simulations for fully autonomous and semi-autonomous FRC swerve-drive systems.
05

Contact

Get in touch

I'm always happy to talk about software engineering, AI systems, robotics, or opportunities to build something great together. The fastest way to reach me is email.

angelofrancislandiza@gmail.comDownload resume