I build systems that think, automate, and scale

About

I recently graduated from UC Davis with a B.S. in Computational Cognitive Science (Data & AI) and a minor in Philosophy focused on AI Ethics, with a 3.8 GPA. I'm currently building AI receptionists at Nudge AI in San Francisco, working on real-time voice agents for healthcare.

Previously, I deployed voice AI agents across 4 countries at Everise, built automated refund flows and predictive fault systems at Blendid AI, and integrated LLM-powered chatbots at the CK Birla Group.

Outside of engineering, I founded the Machine Learning Student Network at UC Davis, a community I scaled to 50+ members, where I mentor students through end-to-end ML project development and deployment.

When I'm not coding, I'm probably deep in a chess endgame, hiking somewhere with terrible cell service, or writing about AI on Substack. Currently open to full-time opportunities in AI/ML engineering.

Experience

January 2026Present

Software Engineer, AI·Nudge AI

San Francisco, CaliforniaInternship

Building production AI receptionists for healthcare clinics, handling real-time voice interactions with sub-500ms latency and HIPAA-compliant patient intake.

  • Productionized AI receptionist over LiveKit & ElevenLabs at sub-500ms end-to-end latency with barge-in handling
  • Wired LangGraph tool-calling agents with guardrails and MCP servers for HIPAA-aware patient intake workflows
  • Instrumented Braintrust eval pipelines with trajectory tests and tool-call accuracy checks for agent reliability
June 2025October 2025

Technical Support Engineer·Blendid AI

Sunnyvale, CaliforniaInternship

Built automation tools for a robotics food company, handling refunds, inventory alerts, and machine health monitoring across 15 kiosk locations.

  • Owned end-to-end product launch of automated refund flows, slashing ticket resolution latency 72% for 15 sites
  • Orchestrated B2B inventory alerting platform, driving cross-functional ops alignment for 99% recipe availability
  • Defined core system health metrics and launched predictive fault features, slashing operational false alarms 20%
June 2024December 2024

Software Engineer, Voice AI·Everise

Plantation, FloridaInternship

Deployed Retell AI voice agents across 4 global IT support centers, authoring prompt and tool-calling logic for live knowledge base retrieval.

  • Rolled out Retell AI voice agents across 4 global IT support centers, automating 70% of internal call resolutions
  • Authored prompt and tool-calling logic for IT support agents, wiring internal knowledge bases for live retrieval
  • Tuned voice agent reliability with low-latency targets and iterative prompt loops across 4 country deployments
June 2023December 2023

Software Engineer, AI·CK Birla Group · Healthcare & IVF

Gurugram, HaryanaInternship

Built an internal AI chatbot that could answer employee questions by reading company documents, and sped up the backend APIs powering it.

  • Integrated LLM-powered chatbots via LangChain and Flask for internal Slack-based question answering workflows
  • Curated PDF text datasets for iKites.ai to enable efficient company-wide automated question answering systems
  • Minimized API latency by 25% for employee queries by optimizing Flask and Node backends with data extraction
March 2024September 2025

Tech Director, Founding Member·Machine Learning Student Network

Davis, California

Founded and grew a 50-member ML club at UC Davis, mentoring student teams through building and deploying real machine learning projects.

  • Founded UC Davis ML Student Network, scaling to 50 members and mentoring 6 juniors on end-to-end ML builds
  • Guided 5-person student cohorts from ideation to complete deployment of ML systems with end-to-end CI/CD pipelines
  • Trained real-time ASL recognizers via MediaPipe and MobileNetV2 to 90%+ accuracy on automated evaluations
View Full Résumé

Projects

The Modelling Directory

Production web platform for the modelling industry with multi-role auth, messaging, agency pipelines, and hardened security across 11 Django apps.

A full-stack platform where models, agencies, and clients can connect — with secure messaging, application workflows, and proper identity protection.

  • Shipped production web platform with multi-role auth, email verification, and onboarding across 11 Django apps
  • Engineered messaging system with request/accept/block workflows and agency application pipeline with snapshots
  • Hardened platform security with CSRF, rate limiting, IDOR protection, PII anonymization, and 255 test cases
Django 6.0PostgreSQLTailwind CSSCloudflare R2Render

Enterprise KG-RAG w/ Multi-Agent Layer (Graphiti)

Enterprise knowledge graph RAG system for financial PDFs with structured entity extraction, graph-backed retrieval, and evidence-bound multi-agent answering.

Think of it as a smart filing cabinet for financial documents that maps relationships between companies and dates, then answers questions only with evidence it actually found.

  • Led enterprise KG-RAG product strategy, utilising Neo4j to extract complex financial entities from PDF data
  • Enforced AI reliability by designing 5-agent CrewAI pipelines with strict evidence-only JSON output protocols
  • Deployed Graphiti on Neo4j Aura, leveraging product telemetry and vector indexes for real-time visual graphs
  • Formalised financial domain modelling, building typed Neo4j edges to capture precise dates in enterprise filings
Neo4jCrewAIDockerReact

Bullseye: AI Financial News Analysis Platform

Real-time financial news analysis platform combining GPT-4 article understanding, Chrome extension workflows, and live market context across 200+ sources.

A Chrome extension that reads the financial article you are on, runs it through GPT-4, and gives you a plain-English summary with market charts in one click.

  • Synthesised real-time market analysis product pipelines, integrating GPT-4 APIs to deliver user news insights
  • Launched Chrome extension product features, triggering seamless LLM analysis across 200+ financial portals
  • Constructed interactive frontend UX with React and TS, embedding SVG charts for market data comparisons
OpenAI APIMySQLAlpha VantageNode.jsReactTypeScript

Echo Journal: AI Voice Journaling iOS App

AI voice journaling app with realtime transcription, async backend processing, and structured daily reflection generation.

You talk to your phone like a voice memo, and it turns that stream of thought into a structured journal entry with AI-generated reflections and insights.

  • Handled iOS scaling for 100+ concurrent OpenAI Realtime API connections with sub-second audio latency
  • Supervised backend product architecture via FastAPI and async PostgreSQL to power AI-driven journal synthesis
  • Prototyped iOS MVP roadmap and conducted local beta testing to validate core AI voice journaling UX workflows
SwiftUIFastAPIWebSocketPostgreSQLOpenAI API

NoAudience

Local-first desktop media tracker built with Tauri v2 and SvelteKit, storing everything in SQLite with Drizzle ORM — no cloud, no accounts.

A desktop app for tracking movies, shows, and books that keeps all your data local on your machine — no sign-ups, no cloud sync, just yours.

  • Built local-first desktop app with Tauri v2 and SvelteKit for private media tracking with zero cloud dependencies
  • Designed SQLite schema with Drizzle ORM for efficient querying across media types with full offline support
Tauri v2SvelteKitSQLiteDrizzle ORM

Relatient Appointment Pathway

Healthcare voice agent for appointment scheduling with prompt-injection defences, entity capture, and reliable multi-turn conversation handling.

An AI phone agent that schedules doctor appointments, designed to resist manipulation and reliably handle real conversations.

  • Built prompt-guarded voice flows for appointment booking, including zero-shot handling for names, dates of birth, and scheduling intents
  • Combined phonetic parsing with context-aware prompting to reduce hallucinated transfers and improve captured caller details
Bland AIPrompt InjectionZero-Shot LearningLLM Security

Deep Q-Learning: Atari Pong

Deep reinforcement learning agent for Atari Pong using convolutional Q-networks, replay buffers, and target-network training.

I trained an AI to play Pong from raw pixels until it could consistently learn winning behaviour through trial and error.

  • Implemented a convolutional DQN in PyTorch with epsilon-greedy exploration, target networks, and experience replay for stable Atari training
  • Optimised preprocessing and training with frame stacking, reward clipping, and CUDA-backed batches to improve sample efficiency
PyTorchOpenAI GymCUDAOpenCV

ChatCKB: CK Birla AI Chatbot

Internal document Q&A assistant built with GPT-4, LangChain, and Flask for answering employee questions from company PDFs.

Employees could ask a question in plain English and get an answer from company documents instead of digging through PDFs themselves.

  • Built a retrieval-backed internal chatbot with LangChain, Flask, and GPT-4 to answer employee questions against company documents
  • Created ingestion and query pipelines that extracted PDF content, chunked knowledge, and served responses through a lightweight internal interface
OpenAI APILangChainPythonGPT-4Flask

Real-Time ASL Recognition

Real-time computer vision pipeline for translating ASL gestures to text with MediaPipe tracking and MobileNetV2 inference.

Point a webcam at someone signing and the system translates the hand signs to text in real time.

  • Trained a transfer-learning pipeline on MobileNetV2 with MediaPipe landmarks to classify ASL gestures from live webcam input
  • Optimised inference with quantisation and efficient preprocessing to keep recognition responsive on edge hardware
TensorFlowMediaPipeOpenCVMobileNetV2

Connect4 Championship

Game-playing AI using Minimax, alpha-beta pruning, and heuristic board evaluation for tournament-scale competition.

I built a Connect 4 AI that looks several moves ahead and competed against more than 250 other agents in a class tournament.

  • Implemented Minimax with alpha-beta pruning and board evaluation heuristics to search several moves ahead under time limits
  • Tuned move ordering and scoring logic to cut decision latency and improve play against a large field of competing agents
PythonPyGameMinimaxAlpha-Beta Pruning

Skills

Product

Agile/Scrum
A/B Testing
Product Roadmapping
Telemetry
User Experience (UX)
PRDs
Stakeholder Management
Jira
Confluence
Figma
Tableau
Postman

Languages

Python
SQL
Java
C/C++
TypeScript
Rust
Golang
JavaScript
R
HTML/CSS
Bash
x86

ML & AI

Generative AI
LLMs
Voice Agents
RAG
LangGraph
MCP
LLM Evals
Vector Databases
Guardrails
Prompt Engineering
NLP
Knowledge Graphs
LangChain
TensorFlow
Keras
Scikit-learn
Pandas
NumPy
Seaborn
OpenCV
Stardog
Apache Jena Fuseki

Technologies

React
Node.js
Express
Flask
FastAPI
Django
PostgreSQL
MySQL
Neo4j
MongoDB
Redis
AWS (S3, EC2, Bedrock)
GCP
Azure
LiveKit
ElevenLabs
WebRTC
Tailwind CSS
GraphQL
gRPC
Spring Boot
Airtable

Tools & Infrastructure

Git
GitHub Actions
Jenkins
Docker
Kubernetes
Terraform
Maven
CI/CD
WebSockets
Zendesk Webhooks
DevOps

Writing

Minds to machines, and everything in between

View all posts on Substack