AI Data Engineer

TalentOla•New York City, NY

About The Position

This role focuses on building and deploying AI-powered data solutions. The ideal candidate will have a strong background in data engineering, Python development, and cloud platforms, with a specific emphasis on developing LLM-powered applications and understanding AI agent engineering patterns. The position requires hands-on experience in building production-grade data pipelines, working with various data platforms, and applying software engineering best practices.

Requirements

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.

Nice To Haves

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.

Responsibilities

Develop and deploy AI-powered data solutions.
Build production-grade data pipelines.
Develop LLM-powered applications.
Integrate LLMs with enterprise data platforms.
Work with APIs, databases, data platforms, and enterprise data sources.
Apply strong software engineering fundamentals including Git, testing, CI/CD, and production deployment.
Work independently and take ownership from requirements through delivery.
Troubleshoot and communicate effectively.

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