AI Data Engineer – Generative AI, Scalable Data Pipelines

Pakistan Single Window (PSW)

AI Data Engineer focusing on building ETL pipelines and maintaining data infrastructure for large-scale AI applications. Collaborating with cross-functional teams for AI model deployment and monitoring.

Posted 7/23/2026full-timeRemote • 🇵🇰 PakistanJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing ETL pipelines for AI applications, utilizing Python, PySpark, SQL, and cloud services. Proficient in deploying AI applications with FastAPI and Docker while ensuring data security and compliance.

Highest-signal resume keywords

ETL Pipeline DevelopmentPython ProgrammingCloud Services (AWS, Azure, GCP)Vector Databases (FAISS, ChromaDB, Pinecone)Containerization (Docker, Kubernetes)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL Pipeline DevelopmentPython ProgrammingPySparkSQLCloud Services (AWS, Azure, GCP)Vector Databases (FAISS, ChromaDB, Pinecone)FastAPIStreamlitDockerKubernetes

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaboration Abilities

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Data EngineeringMaster's Degree in Artificial Intelligence

Industry Keywords

AI ApplicationsData EngineeringReal-Time Data ProcessingRetrieval-Augmented Generation (RAG)Data SecurityAI Model Reliability

Tech Stack

Tools & technologies

AWSAzureCloudDockerETLGoogle Cloud PlatformKubernetesPandasPySparkPythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Pakistan Single Window (PSW) Website LinkedIn All Job Openings 51 - 200 employees Founded 2021 🤝 B2B 📋 Compliance 🏛️ Government B2B
Compliance
Government Pakistan Single Window (PSW) is an integrated digital platform designed to streamline cross-border trade in Pakistan. It enables parties involved in trade to submit standardized information and documents through a single-entry point to meet all import, export, and transit-related regulatory requirements. PSW aims to reduce the time and cost of doing business by digitalizing Pakistan’s cross-border trade processes and eliminating paper-based manual procedures. It integrates commercial banks, customs, and other government agencies on a unified digital platform to facilitate financial transactions, regulatory compliance, and the electronic processing of licenses, permits, and certificates. Its Tradeverse portal offers a single access point for trade information related to imports, exports, and transit, enhancing the efficiency and transparency of trade operations in Pakistan. AI Data Engineer – Generative AI, Scalable Data Pipelines Job not on LinkedIn 🔥 39 minutes ago 🇵🇰 Pakistan – Remote ⏰ Full Time 🟢 Junior 🟡 Mid-level 🚰 Data Engineer AWS Azure Cloud Docker ETL Google Cloud Platform Kubernetes Pandas PySpark Python SQL Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 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. 🎯 Requirements
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.
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