Hi, I'mYash Sanghvi
Software Engineer specializing in AI/ML, Full-Stack Development, and building production systems with containerized ML pipelines.
Who I Am
Software Engineer passionate about AI infrastructure, machine learning, and robotics systems. Currently building production AI solutions at Quantea and TEAMCAL AI while pursuing my degree at Santa Clara University. I specialize in cloud architecture, containerized ML deployments, and embedded control systems.
Education
Santa Clara University
B.S. Computer Science and Engineering
Expected May 2027
Stony Brook University
Computer Science
Aug 2024 - Jun 2025
Silicon Valley Career Technical Education Center
Mechatronics, Robotics, and Automation Engineering
Aug 2023 - Jun 2024
Experience
Work Experience
My professional journey and contributions to various organizations.
AI Infrastructure Engineer Intern
Quantea
- •Orchestrating containerized environments using Kubernetes and Docker for the 'AI Infrastructure in a Box' product, managing a 4-GPU cluster to ensure seamless ML model deployment.
- •Spearheaded a cloud migration from iPage to Cloudways, optimizing server configurations to slash Largest Contentful Paint (LCP) from 15s to <1s, significantly boosting page performance.
- •Maintaining technical product specifications on the live web portal to ensure accurate documentation for AI hardware and infrastructure capabilities.
Undergraduate Research: NLP & Transformers
Santa Clara University - Trustworthy Computing Lab
- •Conducting directed research under Prof. Yuhong Liu at the Trustworthy Computing Lab.
- •Focusing on Deep Learning concepts including Transformers and Natural Language Processing (NLP).
- •Investigating robustness and security within AI/ML architectures.
AI & Machine Learning Software Engineer Intern
TEAMCAL AI
- •Migrating legacy web interfaces to a modern MVC architecture, refactoring the codebase to improve modularity and support autonomous multi-calendar planning features.
- •Implemented Agile/Scrum workflows by integrating Jira with GitHub, establishing structured CI/CD version control to streamline the engineering lifecycle.
- •Architected a production-mirroring local environment using Apache Virtual Hosts and PHP (CodeIgniter), significantly reducing deployment errors.
Competitions
Awards & Competitions
Competitive achievements and recognitions.
Agent Watch — Real-Time AI Agent Observability
AWS x Anthropic x Datadog Hackathon
- •Built a real-time observability and reliability platform that provides full visibility into AI agent actions before any tool executes, running three checks on every call: behavior analysis, security enforcement, and cost/performance tracking.
- •Engineered a Neo4j policy graph for security enforcement that controls exactly which tools an agent can use and with what parameters, and a behavior layer that cross-references input intent with output to catch hallucinations, misinterpretation, and drift.
- •Stress-tested against prompt injections, data exfiltration, social engineering, and cost spike attacks—Agent Watch caught every one. Built on AWS Bedrock with Anthropic's Claude, tracking 15+ metrics in real time on a Datadog dashboard.
Sentinel SDK — Runtime Security for AI CLIs
Google DeepMind Continual Learning Hackathon
- •Built Bastion Guard with Abraham Bhatti—a three-stage security pipeline (Triggers, Checks, Enforcement) that intercepts, evaluates, and safely executes every tool call from agentic AI CLIs like OpenCode, Claude Code, and Aider.
- •Engineered a system that detects risky commands in real-time, consults an LLM-bootstrapped rule set with persistent JSON memory of past decisions, and enforces four outcomes: execute, kill, reroute to LLM for safer rewrite, or suggest an alternative.
- •Integrated Akash Network for distributed LLM inference at scale, Composio for real-time logging to GitHub, and You.com Search API for live context on flagged commands—ensuring the guard cross-checks against current docs, not stale training data.
Robotics, Urban Search and Rescue
SkillsUSA California
- •Achieved 1st place in the regional SkillsUSA Urban Search and Rescue Competition and top 10 in State.
- •Spearheaded the design and development of a sophisticated robotic solution capable of navigating obstacles and retrieving objects, such as a cube from a simulated mailbox environment.
- •Invested over 120 hours in the meticulous engineering process, ensuring the robot's competitiveness and readiness for high-stakes competition.
Projects
Featured Projects
A selection of my recent work and personal projects.
SF Quest (Golden Gate Quest)
A gamified mobile web app enabling users to discover San Francisco through personalized photo-based treasure hunts. Features AI voice guide powered by Pipecat, historic photo comparisons, and personalized itineraries based on user preferences. Uses RAG with NeMo Embeddings and CuVS Vector Search.
Autonomous Scheduling Assistant
An intelligent voice-enabled scheduling assistant powered by LangGraph and GPT-4o-mini. Features natural language processing, Google Calendar two-way sync, smart conflict detection, context-aware memory, and multi-platform support for Zoom, Teams, and Google Meet.
Highlight Generator
Auto-generate basketball highlight reels with AI narration. Uses YOLO11n tracking with 7-signal scoring (motion, acceleration, jumps, size, centrality, persistence, pose) to identify key players, auto-crops to 9:16 vertical format, and adds AI-generated sports commentary via Gemini and OpenAI TTS.
SafePath
Full-stack safety navigation analyzing real-time SF crime & 311 incident data to recommend the safest walking routes. Features time-decay risk scoring algorithm (72hr for high-risk, 24hr for low-risk incidents), 200m safety buffer detection, and offline route optimization with waypoint injection.
PortPlateAI
Comprehensive data analytics dashboard for California's top agricultural commodities. Features interactive Recharts visualizations, AI-powered natural language query interface (LangGraph-ready), and spoilage simulation with temperature/transportation delay modeling and economic loss estimation.
Robotic Motion Control System
Designed and 3D-printed 4+ robotic subsystem prototypes integrating servo/motor assemblies for autonomous actuation. Programmed C++ control logic to automate motion, sensor polling, and test workflows, reducing manual validation time by ~40%. Performed electromechanical stress testing improving response consistency by 25-35%.
Skills
Technical Skills
Technologies and tools I work with.
Agentic AI & LLM Systems
Building autonomous AI agents with memory, tool-use, and multi-step reasoning
Production ML Infrastructure
Deploying and maintaining GPU clusters for ML model serving at scale
Languages
AI/ML & Computer Vision
Cloud & Infrastructure
Full-Stack Development
Hardware & Embedded
Certifications
Licenses & Certifications
Professional certifications and credentials I've earned.
UAV PART 107
Federal Aviation Administration
Issued Jun 2024 · Expires Jun 2029
Devtools Pro: Beginner to Expert w/ Chrome Developer Tools
Udemy
Issued Dec 2025
Credential ID: UC-222fe103-e042-4cb3-afdc-023a58cd622a
CodePath Intermediate Technical Interview Prep (TIP102)
CodePath
Issued Spring 2025
Credential ID: 114914
Generative AI for Java Developers with Azure OpenAI ChatGPT
Udemy
Issued Feb 2025
Credential ID: UC-f74b562b-f236-4d35-a970-5f118e8e7012
Contact
Get In Touch
I'm currently open to new opportunities. Whether you have a question or just want to say hi, feel free to reach out!
Contact Information
I typically respond within 24-48 hours. For urgent matters, please reach out via LinkedIn or email directly.