Data AI Engineer

Compunnel

$90K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
  • 7+ years of experience in Data Engineering, Cloud Engineering, or AI Engineering.
  • Strong hands-on experience with AI-powered applications and AI Agents.
  • Familiarity with Large Language Models (LLMs) such as GPT, Claude, or similar.
  • Proficient in Python and data engineering frameworks.
  • Experience with cloud platforms like AWS, Azure, or Google Cloud Platform (GCP).
  • Knowledge of structured and unstructured data processing.

Responsibilities

  • Design, build, and deploy intelligent AI Agents using modern frameworks.
  • Develop and maintain scalable data pipelines and integration solutions.
  • Build, optimize, and support cloud-native AI and data platforms.
  • Integrate AI solutions with enterprise applications and APIs.
  • Design and implement Retrieval-Augmented Generation (RAG) architectures.
  • Collaborate with stakeholders to translate requirements into solutions.
  • Monitor, troubleshoot, and optimize AI models and data pipelines.

Benefits

  • Flexible working hours and remote work options.
  • Access to professional development and training programs.
  • Health and wellness benefits including mental health support.
  • Opportunities for career advancement and skill development.
Full Job Description
Job Summary

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.

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