Wenhao He (Jacky)
Ready to Build, Scale, and Innovate
Software Engineer based in New York with nearly 2 years of startup experience across full-stack development, AWS-backed systems, and production feature delivery
About Me
Experience
Built and shipped full-stack React, TypeScript, and GraphQL features across order management, customer accounts, and purchasing flows for a B2B wholesale platform serving daily production traffic.
Integrated the Stream Chat API for real-time messaging, supporting 500+ concurrent users across web and mobile in production.
Wrote Jest tests across ordering, products, promotions, vendors, POs, returns, accounting, and team modules, reaching 90%+ branch coverage and catching regressions before they hit production.
Set up Husky pre-commit and pre-push hooks to enforce linting, formatting, and build checks across the team, catching issues before they entered code review.
Owned the React Native mobile app (JavaScript, Firebase, Azure) from kickoff through launch, delivering profile, rewards, payments, and job board features for 300+ members.
Added job browsing, description pages, and a posting submission flow so members could find and share opportunities in-app.
Plugged in Azure Form Recognizer to auto-extract fields from uploaded job description PDFs, saving users from re-typing everything manually.
Compressed and resized profile images before writing them to Firebase, which dropped load times from minutes to seconds.
class SoftwareEngineer: def __init__(self): self.name = "Wenhao He" self.role = "Software Engineer" self._email = "wenhaohe8@gmail.com" self.education = [ "M.S. in Artificial Intelligence — University at Buffalo (SUNY)", "B.S. in Computer Science — University at Buffalo (SUNY)", ] self.experience = [ "Software Engineer @ Clipp — New York, NY", "Software Engineer @ CAN International — New York, NY", ] self.stack = { "languages": ["Python", "TypeScript", "JavaScript", "C/C++", "C#", "Java", "Go"], "frontend": ["React", "Next.js", "React Native", "Angular", "Tailwind"], "backend": [".NET", "Node.js", "Express", "Flask", "Spring", "GraphQL"], "databases": ["MySQL", "PostgreSQL", "MongoDB", "DynamoDB", "Redis"], "ai_ml": ["LLMs", "RAG", "Transformers", "TensorFlow", "PyTorch"], "cloud": ["AWS", "Terraform", "Docker", "Kubernetes", "GCP", "Azure"], } @property def current_focus(self): return "Building scalable full-stack & AI-powered solutions" def __repr__(self): return f"{self.name} | {self.role}"
Skills
Programming
Developing scalable solutions across low-level systems and high-level scripting.
AI & Machine Learning
Building intelligent systems with LLMs, RAG pipelines, and ML/DL frameworks for NLP and beyond.
Cloud & DevOps
Deploying and managing scalable, containerized applications on cloud platforms with IaC and orchestration.
Frontend & UI
Developing dynamic, high-performance web and mobile applications with modern frameworks.
Backend & Databases
Designing secure, efficient backends with REST APIs, GraphQL, and relational/NoSQL databases.
Deployment, Testing & Tools
Streamlining CI/CD pipelines, testing, and developer workflows.
Projects
ResumeMatch
Serverless AI resume analyzer built on AWS. Designed an event-driven pipeline (S3 → Lambda → Textract → Bedrock) for 4-pass LLM analysis including keyword extraction, match scoring, and resume rewriting. Deployed as a React/TypeScript SPA with Cognito auth, DynamoDB persistence, and CloudFront delivery.
Movie Recommendation System
Built an AI-powered movie recommendation system using Transformer models & TMDb metadata for personalized content. Engineered a scalable ML pipeline with AWS S3 & SageMaker for real-time inference & deployment.
Audio Cloning
Developed a deep learning project to clone a judge's voice, enabling it to narrate the decision from the Brown v. Board of Education civil rights case. Implemented advanced speech synthesis techniques for realistic voice generation.
Monocular Depth Estimation
Implemented encoder-decoder CNN architecture for estimating 3D distances from 2D images. The system can predict depth information from a single image, enabling applications in robotics, autonomous vehicles, and augmented reality.
Fruit/Vegetable Detection
Conducted a Computer Vision project to detect various fruits and vegetables in 2D images. The system can identify 30+ different produce items with high accuracy, supporting applications in retail automation and agricultural technology.
Blog
Technical Blog
Deep dives into Machine Learning fundamentals and System Design patterns. From neural networks to transformers, and from video streaming to ticketing platforms, explore practical insights and architectural solutions.