Building intelligent, scalable systems
I architect backend modules, integrate LLM/RAG pipelines, and ship reliable data & ML workflows for enterprise-scale platforms.
About
Results-driven engineer focused on bridging research with production for document intelligence and automation. Comfortable across data engineering, backend APIs, and ML systems.
Experience
AI Software Engineer Intern
- Architected backend modules to deploy LLM-based NLP with LangChain & RAG for contextual document querying.
- Designed pipelines supporting fine-tuning with private corpora and integrated internal evaluation suites.
- Integrated semantic validation / human-in-the-loop review to increase trust in enterprise workflows.
- Built ETL pipelines (Python, Airflow) to normalize & vectorize documents for semantic search.
AI SWE & Research Assistant
- Engineered cloud-native APIs for cyberviolence detection with LLMs and fine-tuned classifiers (Azure).
- Developed RAG pipelines with vector search and LangChain toolchains for sensitive content detection.
- Built multi-stage NLP workflows including prompt engineering and evaluation frameworks.
- Automated PEFT/LoRA experimentation for resource-constrained GPUs.
Data Science Researcher
- Led research & engineering for large-scale text classification and content safety.
- Designed evaluation pipelines and reproducible experiments for NLP models.
Teaching Assistant (Multiple Courses)
- Guided students across ML, discrete math, and advanced programming with hands-on labs and reviews.
Skills
Python
Backend Development
NLP
LLMs & RAG
LangChain
SQL
NoSQL (Elasticsearch, MongoDB)
Airflow
Azure
ETL/ELT
Snowflake
Databricks
Spark
Data Visualization
Education
Concordia University
Shahid Beheshti University
Contact
Montreal, Quebec, Canada