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AI Data Engineer at Pakistan Single Window
Islamabad, Islamabad Capital Territory, Pakistan -
Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, PySpark, SQL, ETL Pipelines, Cloud Services, Data Infrastructure, Real-Time Data Processing, Vector Databases, Containerization, Orchestration Tools, API Development, Data Security, Compliance, Problem-Solving, Collaboration, Communication

Industry

IT Services and IT Consulting

Description
Build and optimize ETL pipelines for large-scale AI applications, integrating APIs, web scraping, and real-time data processing. Develop and maintain scalable AI data infrastructure using PySpark, Pandas, SQL, and cloud services (Azure, AWS, GCP). Implement retrieval-augmented generation (RAG) pipelines using FAISS, ChromaDB, and Pinecone for AI-driven insights. Deploy and monitor AI applications using FastAPI, Streamlit, Docker, for real-time performance. Work with cross-functional teams to ensure data security, compliance, and AI model reliability in production environments. Bachelor's or Master's degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field. Atleast 2-4 years of experience in data engineering, AI/ML, or cloud-based AI infrastructure. Expertise in Python, PySpark, and SQL for data transformation and large-scale processing. Experience with cloud platforms (AWS, Azure, GCP) for AI model deployment and data pipeline automation. Hands-on experience with vector databases (FAISS, ChromaDB, Pinecone) for efficient data retrieval. Proficiency in containerization and orchestration tools like Docker and Kubernetes. Strong understanding of retrieval-augmented generation (RAG) and real-time AI model deployment. Knowledge of API development and AI service integration using FastAPI and Streamlit/Dash. Ability to optimize AI-driven automation processes and ensure model efficiency. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities.
Responsibilities
Build and optimize ETL pipelines for large-scale AI applications and develop scalable AI data infrastructure. Deploy and monitor AI applications for real-time performance while ensuring data security and compliance.