AI Engineer

Open to full-time
Bio

Riyyan A is an AI Engineer with several years of experience in building intelligent systems and applications, particularly within the HealthTech and SaaS sectors. Riyyan's core stack includes Python, FastAPI, Flask, and Django for backend development, while utilizing React and Angular for frontend interfaces. He is adept in machine learning and data processing using PySpark, Scikit-learn, and TensorFlow, focusing on real-time data accuracy and scalable AI systems. His work also involves cloud and DevOps practices with AWS, Docker, and CI/CD tools. Notable projects include developing the VisioHear application, which translates Pakistan Sign Language into text and speech using the MERN stack and TensorFlow for real-time recognition, and the AI Voice Medical Receptionist, which automates patient call handling and appointment scheduling using VAPI and Twilio. His contributions to healthcare systems have involved processing over 600,000 patient records to identify chronic disease risk hotspots. Riyyan holds a Bachelor of Science in Information Technology from the University of the Punjab, Lahore. He is best suited for roles that involve designing and deploying AI-driven solutions, particularly in healthcare and customer service automation.

Expertise
FlaskMongoDBPySparkGitJavaScriptPythonAngularReactAWSTypeScriptFast APIPHPNode.jsSQLPyTorchJavaHTMLCSSBash
Video Intro
Assessments
APPLICANT AVG · 55%RIYYAN · 87%0255075100TopASSESSMENT SCORE (0–100)

General Coding and Video Assessment

(87/100)
  • Implement LRU Cache AlgorithmMedium
  • Understanding Rate Limiting in APIsEasy
  • Ensuring Real-time Data Accuracy in Mobile AppMedium
Projects

VisioHear – Vision-based Pakistan Sign Language & Speech Interpretation

Developed an AI-powered web application to translate Pakistan Sign Language (PSL) into text and speech, improving accessibility for differently-abled individuals. Built using the MERN stack and integrated TensorFlow Object Detection for real-time sign recognition. Fine-tuned AI and Computer Vision models, including YOLOv5, Faster R-CNN, EfficientDet-D0, MobileNet-SSD, and LSTM. Created a chatbot using LangChain, fine-tuned on custom FAQs data and integrated with OpenAI APIs, to assist users with adaptive, intelligent responses. Implemented Redux for state management and Mongoose for efficient data handling. Led team collaboration, managing task distribution, timelines, and technical communication. Engineered core backend features including schema design, API integration, authentication systems, and robust testing workflows.

Ethical AI & Bias Detection

Developed a Multi-Agent System using LangGraph, Flask APIs & scikit-learn to detect and mitigate algorithmic and data biases in healthcare AI systems. The system ensures ethical compliance through fairness metrics, real-time analysis, and a roadmap for transparent and inclusive AI development.

Medical Perplexity System

Developed a clinical decision support system that classifies medical queries and routes them to specialized tools for data extraction. The retrieved data is then processed by a final language model to generate accurate, clinically-backed responses.

Liver Lab Outcome Prediction

Developed and evaluated multiple machine learning models (classification + regression) on a dataset of 500,000+ patients to predict liver disease progression. The project focused on early diagnosis by leveraging key health indicators and applying robust data preprocessing and ensemble modeling techniques.

Nexus Patient Module

Enhancements in the local Nexus Project by developing real-time PySpark ETL pipelines and FastAPI-based microservices for efficient data flow across multiple hubs. The project aimed to streamline data processing and improve scalability within healthcare systems.

Public Health Analysis

Analyzed over 600k patient records across U.S. states to proactively identify chronic disease risk hotspots using advanced data preprocessing and statistical analysis. The project provided key public health insights by mapping disease trends and supporting preventive care strategies.

AI Voice Medical Receptionist

A fully automated AI-powered voice receptionist for clinics and hospitals that handles inbound patient calls end-to-end; collecting essential information, and seamlessly scheduling appointments with the relevant doctors. The system supports multiple languages, making it accessible to a diverse patient base. It is equipped with intelligent tools that allow it to verify and cross-check patient data directly from the database in real time, ensuring accuracy throughout the conversation. The system delivers a smooth, human-like experience. A dedicated Admin Dashboard provides clinic staff full visibility and control over call recordings, patient data, and appointment management; all in one place.

AI-Powered Call Center Coaching System

A Multi-Agent System that automatically analyzes call center agent conversations against key KPI metrics. The system evaluates each call, identifies performance gaps, and autonomously generates personalized coaching and training recommendations for each agent; helping them understand their weaknesses and continuously improve without requiring manual supervisor intervention.

Experience

  1. Software Trainee AI Engineer

    CureMD, Lahore· HealthTechJul 2024 — Dec 2024
    • Completed 40+ MOOCs covering advanced mathematics, statistics, programming
    • Led and completed three key projects in Machine Learning and Deep Learning
    • Awarded Gold Medal for securing first position and Best capstone out of 12 projects.
    LangGraphChromaDBScikit-learnPandasFlaskSocket ProgrammingReactJavaScriptPythonPopplerClassification & RegressionMongoDBDjango

  2. Associate AI Engineer

    CureMD, Lahore· HealthTechJan 2025 — Jun 2026
    • Preprocessed 600,000+ multi-state U.S. patient records for chronic disease risk hotspots extraction
    • Researched and contributed to the early-stage development of local Medical Perplexity by building a language-based router to direct clinical queries to appropriate diagnosis or treatment tools.
    • Contributed to local Nexus Project enhancements by implementing real-time PySpark ETL pipelines and FastAPI-based micro-services for different modules of Nexus.
    Fast APIPrompt EngineeeringPyspark ETLMongoDBJWT O2 AuthPandasTypeScriptLinux

  3. AI Engineer

    CureMD, Lahore· HealthTechJul 2025 — Present
    • Currently working on the advancement of the local Medical Perplexity System, enhancing routing logic and refining tools logic to support diagnosis and treatment recommendations.
    • Focused on aligning clinical workflows with language-based tools using large-scale healthcare data and query analysis.
    OllamaLlama & QwenMilvusMCPAngularAzure DevopsGitFast APIPrompt Engineering

  4. AI Engineer & Team Lead

    Crixent· Enterprise & SaaSNov 2025 — Present
    • Leading a team of two, to handle multiple client projects
    • Built a multilingual AI voice medical receptionist using VAPI, Twilio, and ElevenLabs that autonomously handles patient calls, verifies records, schedules appointments, and provides staff with a full admin dashboard for call and appointment management.
    • Built an AI-powered Multi-Agent call center coaching system that autonomously evaluates agent performance across KPI metrics and delivers personalized training recommendations to drive continuous improvement.
    VAPITwilioCall.comSQLlitengrokDeepgramOpenAI GPTEleven LabsVADCrewAIRAGDockerWeviatePostgres SQLceleryDigital OceanFast API
Education

  1. Bachelor of Science in Information Technology

    Faculty of Computing & Information Technology (FCIT), University of the Punjab, LahoreLahore2020 — 2024
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