Waleed Mustafa

Software Engineer

Strategic Systems International

Lahore, Punjab

08.2023 - Current

Company Overview: AI & Machine Learning
Automated complex workflows by designing and implementing AI agents. I'm proficient in leading AI agent frameworks, including LangChain, LangGraph, and CrewAI.
Developed and deployed a multi-agent AI system for Retrieval-Augmented Generation (RAG) to analyze and facilitate interactive discussions on thousands of stock-related user tweets.
Implemented a multi-agent AI-powered chatbot backend providing comprehensive functionalities, including reservation management, on-demand logo, letterhead, and business card generation, personalized user reminders, PayPal-integrated payment transfers, email communication, and monthly spending tracking. All interactions were designed for a natural, human-friendly conversational experience.
Implemented a multimodal RAG tool integrating various data formats (podcast audio, videos, PDFs, text) using a hybrid ensemble search approach which can answer questions from any of the sources mentioned. Deployed the system on AWS ECS to handle complex user queries with high accuracy.
Developed a text-based RAG chatbot for a manufacturing client with hundreds of PDF manuals across multiple assembly lines. It answers relevant manual and accurately answer machine‐related queries.
Implemented a domain-specific chatbot for a fintech client using generative AI to provide precise query generation for their query tool.
Created a dataset configuration tool using generative AI to automate the generation of dataset configurations for onboarding new datasets.
Developed ETL pipelines for data ingestion and historical backfilling from various sources such as databases, APIs, and flat files, ensuring data consistency and reliability.
Designed data pipelines using the Snowflake connector in Python, including schema table creation, configuration settings, and external stages, and optimized data transfer from Wasabi to Snowflake.
Conducted extensive data analysis and preprocessing using Python libraries like NumPy and Pandas, transforming data through pivoting, filtering, merging, and other operations.
Implemented time-series data ingestion pipelines for PostgreSQL using Python connectors, debugging and enhancing production databases by testing locally before deployment.
Managed large-scale datasets efficiently using Parquet, HDF5, and Arrow IPC formats, optimizing processing with asynchronous I/O and Python multiprocessing.
Automated the monitoring of data quality and dashboards using Python scripts, alerting on issues to ensure high-quality data management.
Developed containerized Python scripts using Docker for seamless cloud integration, including functionalities for S3 operations and batch processing.
Demonstrated expertise in Bash scripting for automating complex tasks on Linux systems, leveraging advanced Linux commands and system monitoring for resource optimization.