Rutarj Shah

Experience: AI Data Analyst & Model Trainer at Outlier (2025–2025); Cloud Developer / Software Engineer at BCM Corporation (2024–2025). Studied Computer Programming and Analysis at Seneca College.

• Agile
• Amazon Web Services
• Tests automatisés
• Analyse d’affaires
• C#
• CI/CD
• Communication
• CSS
• Service à la clientèle
• Analyse de données
• Saisie de données
• Visualisation de données
• Django
• Docker
• Flask
• Git
• GitHub
• Google Cloud
• Google Workspace
• GraphQL
• HTML
• JavaScript
• Jira
• Kubernetes
• Leadership
• Linux
• Apprentissage automatique
• Microsoft Azure
• Microsoft Excel
• Microsoft Office
• Microsoft Outlook
• Microsoft Word
• MongoDB
• MySQL
• .NET
• Next.js
• Node.js
• Sens de l’organisation
• PostgreSQL
• Power BI
• Résolution de problèmes
• Gestion de produit
• Gestion de projet
• Python
• Assurance qualité
• React
• Redis
• Collecte des exigences
• API REST
• Scrum

1. AI Data Analyst & Model Trainer

   Outlier

   sept. 2025 to déc. 2025

   Remote

   • Developed and deployed inference APIs using LangChain and Python, designing RAG patterns and chunking strategies to process 1,200+ model outputs and improve knowledge bot response quality through continuous prompt refinements and MLOps best practices. • Drove 5+ internal guideline revisions by optimizing RAG applications and indexing strategies, applying Azure OpenAI compatible evaluation frameworks to improve model accuracy and reduce hallucination failures across Gen AI pipelines. • Engineered Python automation scripts integrating vector store compatible embedding workflows and Scikit-learn anomaly detection, cutting processing time by 22% while embracing MLOps coding best practices across distributed Gen AI systems.

2. Cloud Developer / Software Engineer

   BCM Corporation

   avr. 2024 to avr. 2025

   Remote

   • Containerized and deployed 6+ microservices using Docker and Kubernetes on AKS compatible infrastructure, integrating Azure AI Search and vector stores to support Gen AI use case requirements and knowledge bot production monitoring. • Developed REST APIs using Python and PySpark compatible data pipelines, integrating LangChain and Databricks Azure ML style workflows to support Gen AI solutions and machine learning model deployment across cloud environments. • Reduced incident resolution time by 40% through systematic troubleshooting and root cause analysis, supporting production Gen AI applications and continuously improving model accuracy and response quality through feedback driven enhancements.

1. Seneca College

   Computer Programming and Analysis

   Toronto, ON

   2025