Data AI Engineer

Compunnel, Inc.; Columbus (OH); On-site; USD 100,000 - 130,000; Full time

Job summary

Compunnel, Inc. is searching for a highly skilled Data & AI Engineer with hands-on engineering expertise to design and deploy AI solutions. This role demands strong proficiency in data engineering and cloud technologies, focusing on building AI agents and scalable data platforms.

The ideal candidate will possess 7+ years of experience in AI and data engineering, with a solid background in Python, large language models, and cloud platforms such as AWS and Azure. Applicants should be well-versed in data governance and compliance.

Qualifications

• 7+ years of experience in Data Engineering, Cloud Engineering, or related disciplines.
• Experience with Large Language Models such as GPT, Claude, Gemini.
• Strong understanding of structured and unstructured data processing.

Responsibilities

• Design, build, and deploy intelligent AI Agents using modern AI frameworks.
• Develop and maintain scalable data pipelines and data integration solutions.
• Integrate AI solutions with enterprise applications and APIs.

Skills

Strong hands-on experience building AI-powered applications

Proficiency in Python and data engineering frameworks

Experience with AI orchestration frameworks

Experience designing scalable data pipelines

Strong problem-solving and analytical skills

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering

Tools

AWS

Azure

Google Cloud Platform

SQL

NoSQL

Kubernetes

Docker

Job description

We are seeking a highly skilled Data & AI Engineer with strong hands‑on engineering expertise to design, develop, and deploy next-generation AI solutions. The ideal candidate will have proven experience building AI Agents, developing scalable data platforms, and leveraging cloud technologies to deliver enterprise-grade AI and data-driven applications. This role requires a strong blend of Artificial Intelligence, Data Engineering, and Cloud Engineering skills, with the ability to work across the full lifecycle—from data ingestion and model development to AI agent deployment and production support.

Key Responsibilities

• Design, build, and deploy intelligent AI Agents using modern AI and LLM frameworks.
• Develop and maintain scalable data pipelines, data models, and data integration solutions.
• Build, optimize, and support cloud-native AI and data platforms.
• Integrate AI solutions with enterprise applications, APIs, and data sources.
• Design and implement Retrieval-Augmented Generation (RAG) architectures and vector database solutions.
• Develop agentic AI workflows and intelligent automation solutions.
• Collaborate with business stakeholders to translate requirements into scalable AI and data solutions.
• Ensure data quality, governance, security, and compliance across enterprise platforms.
• Monitor, troubleshoot, and optimize AI models, data pipelines, and production workflows.
• Design and implement structured and unstructured data processing solutions.
• Develop and support cloud-native architectures, APIs, and microservices.
• Contribute to AI platform modernization, innovation, and continuous improvement initiatives.
• Stay current with emerging AI, machine learning, data engineering, and cloud technologies.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 7+ years of experience in Data Engineering, Cloud Engineering, AI Engineering, or related disciplines.
• Strong hands‑on experience building and deploying AI‑powered applications and AI Agents.
• Experience working with Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, or similar technologies.
• Strong proficiency in Python and data engineering frameworks.
• Experience with AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar platforms.
• Experience with cloud platforms including AWS, Azure, and/or Google Cloud Platform (GCP).
• Experience designing and implementing scalable data pipelines and ETL/ELT solutions.
• Strong understanding of structured and unstructured data processing.
• Experience with vector databases, embeddings, Retrieval-Augmented Generation (RAG), and prompt engineering.
• Experience developing APIs, microservices, and cloud-native applications.
• Experience with SQL and NoSQL database technologies.
• Strong problem‑solving, analytical, and communication skills.
• Ability to work across the complete AI and data solution lifecycle from design through production deployment.

Preferred Qualifications

• Experience with MLOps practices and AI model deployment.
• Experience with Databricks, Snowflake, or similar modern data platforms.
• Experience with Kubernetes, Docker, and containerized deployment environments.
• Experience with machine learning and deep learning frameworks.
• Cloud certifications in AWS, Azure, or Google Cloud Platform.
• Experience implementing enterprise AI governance and responsible AI practices.
• Experience supporting large-scale enterprise AI and data transformation initiatives.
• Knowledge of modern cloud architecture and distributed computing patterns.