AI Data Engineer

TalentOla; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

TalentOla is seeking an experienced data/ML engineer to design and implement data-powered applications in a cloud environment. You will build scalable data pipelines, integrate with data platforms, and deploy AI-enabled services at scale.

The role requires strong Python skills, hands-on experience with data architectures, and proficiency with Kubernetes, Docker, and CI/CD practices. You will collaborate across teams to deliver robust, production-ready solutions.

Qualifications

• Strong experience in Python application development.
• Strong background in data engineering, data analytics, BI, or data application development.
• Experience with cloud platforms and Kubernetes-based application/pipeline deployment.
• Strong hands-on experience building production-grade data pipelines.
• Strong understanding of data architecture, data processing, ETL/ELT, and data integration.
• Experience working with databases, data warehouses, and/or modern data platforms.
• Experience building data-facing applications or applications that interact directly with data and analytics platforms.
• Hands-on experience developing LLM-powered applications.
• Understanding of AI agent/harness engineering patterns and LLM application architecture.
• Experience working with APIs, databases, data platforms, and enterprise data sources.
• Cloud development experience with Kubernetes-based deployment.
• Strong software engineering fundamentals including Git, testing, CI/CD, and production deployment.
• Demonstrated ability to work independently and take ownership from requirements through delivery.
• Strong analytical, troubleshooting, and communication skills.

Skills

Python programming

Data analytics

ETL/ELT

Data architecture

Independent ownership

Production-grade data pipelines

LLM concepts

AI agent patterns

Tools

Kubernetes

Docker

Git

CI/CD

LangChain

LangGraph

LlamaIndex

Job description

Required Qualifications

• Strong experience in Python application development.
• Strong background in data engineering, data analytics, BI, or data application development.
• Experience with cloud platforms and Kubernetes-based application/pipeline deployment.
• Strong hands-on experience building production-grade data pipelines.
• Strong understanding of data architecture, data processing, ETL/ELT, and data integration.
• Experience working with databases, data warehouses, and/or modern data platforms.
• Experience building data-facing applications or applications that interact directly with data and analytics platforms.
• Hands-on experience developing LLM-powered applications.
• Understanding of AI agent/harness engineering patterns and LLM application architecture.
• Experience working with APIs, databases, data platforms, and enterprise data sources.
• Cloud development experience with Kubernetes-based deployment.
• Strong software engineering fundamentals including Git, testing, CI/CD, and production deployment.
• Demonstrated ability to work independently and take ownership from requirements through delivery.
• Strong analytical, troubleshooting, and communication skills.

Preferred Qualifications

• Experience with agentic AI, LLM orchestration, RAG, or tool-using agents.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.
• Experience with vector databases and retrieval pipelines.
• Experience integrating LLMs with enterprise data platforms.
• Experience building dashboards, analytics applications, self-service data applications, or other data-centric user experiences.
• Experience with AWS, Azure, or GCP.
• Experience with Docker and Kubernetes.