Looking for a job

Asaad khalil

@asaadkhalil

Message

I build high-performance backend, data, and GenAI systems that scale.

Pakistan

Message

What I'm looking for

I'm looking to build scalable backend, data, and GenAI products where I can turn complex ideas into practical automation, improve system performance, and explore new technologies with collaborative teams.

I've built and optimized backend, data, and AI products at Precision, Tkxel, Careem, and Munch:ON. At Precision, I migrated a multi-product platform to a hybrid PostgreSQL and DynamoDB model, reducing API response times by 60% while supporting 5x user load.

I've integrated LLM-powered automation into Chrome and Slack, cut Hale Products API response time by 70%, and built forecasting, RAG, analytics, and cloud automation systems using Python, FastAPI, Golang, AWS, Next.js, and LangChain.

Experience

Work history, roles, and key accomplishments

Current

Software Engineer II

Current

Precision

Dec 2024 - Present (1 year 9 months)

Architected a scalable multi-product data platform by migrating services to a hybrid PostgreSQL and DynamoDB model. Reduced API response times by 60% and led the rebuild of an internal operations dashboard in Next.js 14.

Python Django Next.js TypeScript PostgreSQL DynamoDB AWS REST APIs Terraform

Senior Software Engineer

Tkxel

Apr 2023 - Dec 2024 (1 year 8 months)

Led backend optimization for Hale Products, cutting API response time by 70%. Integrated an LLM-powered backend into Chrome and Slack and migrated legacy Firebase systems to PostgreSQL.

Python fastAPI Next.js React TypeScript PostgreSQL Firebase LLM LangGraph

Software Engineer

Careem

Jul 2022 - Apr 2023 (9 months)

Managed AWS infrastructure including EC2, RDS, S3, and DynamoDB in production. Implemented CI/CD pipelines and deployed Kubernetes workloads for microservices.

AWS Kubernetes Jenkins GitHub Actions Docker Terraform

Software Engineer

Munch:ON

Jul 2021 - Jul 2022 (1 year)

Developed JASPER, a time-series prediction model achieving 70% accuracy in weekly order forecasting. Built and optimized data pipelines using PySpark and MongoDB.

Python PySpark MongoDB Machine Learning Pandas NumPy Time series Forecasting Databricks