Rutarj Shah
Open to opportunitiesAI Data Analyst & Model Trainer at Outlier
Toronto, ON
About
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.
Skills
- Agile
- Amazon Web Services
- Automated testing
- Business analysis
- C#
- CI/CD
- Communication
- CSS
- Customer service
- Data analysis
- Data entry
- Data visualization
- Django
- Docker
- Flask
- Git
- GitHub
- Google Cloud
- Google Workspace
- GraphQL
- HTML
- JavaScript
- Jira
- Kubernetes
- Leadership
- Linux
- Machine learning
- Microsoft Azure
- Microsoft Excel
- Microsoft Office
- Microsoft Outlook
- Microsoft Word
- MongoDB
- MySQL
- .NET
- Next.js
- Node.js
- Organization
- PostgreSQL
- Power BI
- Problem solving
- Product management
- Project management
- Python
- Quality assurance
- React
- Redis
- Requirements gathering
- REST APIs
- Scrum
Experience
AI Data Analyst & Model Trainer
Outlier
Sep 2025 to Dec 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.
Cloud Developer / Software Engineer
BCM Corporation
Apr 2024 to Apr 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.
Education
Seneca College
Computer Programming and Analysis
Toronto, ON
2025