AI Architect (Data Engineering)

Overview

Remote
Depends on Experience
Contract - W2
Contract - Independent
Contract - 12 Month(s)
No Travel Required

Skills

Artificial Intelligence
Amazon SageMaker
Amazon Redshift
Cloud Computing
Cloud Architecture
Data Modeling
Data Engineering
Data Science
Data Warehouse
Database
Data Quality
Google Cloud Platform

Job Details

Job Title: AI Architect (Data Engineering)

Job Duration: Long-Term Contract

Location: Remote

Job Type: Contract

Job Summary:

We are seeking a highly skilled and visionary AI Architect with a strong data engineering background to design, implement, and optimize AI/ML solutions at scale. The ideal candidate will possess in-depth expertise in AI/ML architecture and a solid foundation in modern data technologies, including MongoDB, Snowflake, SQL and NoSQL databases, and data pipelines. This role requires close collaboration with data engineers, scientists, and business stakeholders to architect intelligent systems that drive business outcomes.

Key Responsibilities:

  • Design and develop scalable AI/ML architectures integrated with modern data platforms (e.g., Snowflake, MongoDB).
  • Collaborate with data engineers and data scientists to operationalize ML models in production environments.
  • Lead the development of AI pipelines, model training, validation, deployment, and monitoring.
  • Architect data workflows that ensure data quality, security, and high availability.
  • Identify opportunities to apply AI/ML to business challenges and drive PoCs and pilot projects.
  • Ensure architecture aligns with enterprise standards and compliance requirements.
  • Mentor engineering teams and provide architectural guidance on AI and data solutions.
  • Stay current with emerging technologies and trends in AI, machine learning, and data systems.

Required Skills & Qualifications:

  • Proven experience as an AI/ML Architect or Senior Data Architect with exposure to AI projects.
  • Strong knowledge of data platforms such as Snowflake, MongoDB, PostgreSQL, Redshift, etc.
  • Experience with Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
  • Solid understanding of data modeling, ETL/ELT processes, data lakes, and data warehouses.
  • Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker, Airflow).
  • Excellent communication and leadership skills.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Preferred Qualifications:

  • Master's or Ph.D. in Computer Science, Data Science, AI, or a related field.
  • Certifications in AI/ML or cloud architecture (e.g., AWS Certified Machine Learning, Snowflake SnowPro).
  • Experience in designing real-time AI systems and streaming data solutions (e.g., Kafka, Flink).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.