AI Data Engineer

Hi there! We are South and our client is looking for an AI Data Engineer!

Note to Applicants:

• Eligibility: This position is open to candidates residing in Latin America.

• Application Language: Please submit your CV in English. Applications submitted in other languages will not be considered.

• Professional Presentation: We encourage you to showcase your professional experience by including a Loom video in the application form. While this is optional, candidates who provide a video presentation will be given priority.

• Interview Policy: The use of artificial intelligence (AI) tools during interviews are strictly prohibited. 

• Note: As part of the final stages of our hiring process, candidates may be asked to provide professional references for a reference check. If hired, you may also be asked to update your LinkedIn profile :)

Our client is hiring AI Data Engineers / Architects to join its growing AI Operating Group (AI OG), a team focused on building AI-powered solutions for state and local government, education, and other public sector organizations.

This role sits at the intersection of data engineering, architecture, and artificial intelligence. You will be responsible for designing and building the data infrastructure that powers AI applications, machine learning models, advanced analytics, and generative AI solutions. The ideal candidate combines strong technical expertise with a consulting mindset and enjoys solving complex data challenges in highly regulated environments.

Key Responsibilities

• Design and implement scalable data architectures for AI, machine learning, and analytics workloads
• Build and maintain ETL/ELT pipelines for structured and unstructured data sources
• Develop and manage data lakes, data warehouses, and feature stores to support model training and inference
• Ensure data quality, governance, lineage, and observability across AI data ecosystems
• Collaborate with AI engineers, data scientists, and solution architects to define data requirements and optimize performance
• Design secure and compliant data solutions aligned with public sector standards and regulations
• Implement cloud-native data platforms and modern data engineering frameworks
• Support the development of vector databases and retrieval pipelines for generative AI applications
• Document architectures, data models, metadata, and technical standards
• Evaluate emerging technologies and recommend improvements to existing data platforms

Required Qualifications

• 5+ years of experience in Data Engineering, Data Architecture, or related fields
• Strong experience designing and building scalable data pipelines and platforms for AI/ML use cases
• Advanced proficiency in Python and SQL
• Hands-on experience with modern cloud platforms (AWS, Azure, or GCP)
• Experience with data warehousing, data lakes, distributed processing, and large-scale data systems
• Strong understanding of data modeling, governance, security, and quality management best practices
• Excellent written and verbal English communication skills
• Ability to work independently in a fully remote, U.S.-aligned environment
• Strong problem-solving skills and ability to translate business requirements into technical solutions

Preferred Qualifications

• Experience supporting government, education, or other regulated public sector organizations
• Familiarity with compliance frameworks such as FedRAMP, NIST, or data privacy regulations
• Experience building vector databases and Retrieval-Augmented Generation (RAG) pipelines
• Knowledge of event-driven architectures and real-time data streaming platforms
• Experience working in consulting or client-facing environments
• Cloud or data certifications (AWS, Azure, GCP, Databricks, Snowflake, or equivalent)

Tech Stack

• Python
• SQL
• Apache Spark
• Apache Airflow
• dbt
• Snowflake
• Databricks
• AWS / Azure / GCP
• Kafka
• Delta Lake
• Pinecone
• Weaviate
• Terraform

What Success Looks Like

30 Days

• Gain understanding of MGT’s AI initiatives, data platforms, and active client projects
• Become familiar with internal architecture standards and development workflows
• Contribute to existing data engineering and AI infrastructure efforts

90 Days

• Independently design and implement data pipelines and architecture components for client engagements
• Collaborate effectively with AI engineers and solution architects on production-ready solutions
• Improve data quality, scalability, and operational efficiency across projects

• Lead architecture decisions for complex AI and data initiatives
• Establish best practices for data engineering, governance, and platform design
• Serve as a technical advisor on enterprise AI data strategies and emerging technologies

Core Skills

• Data Architecture & Engineering
• AI & Machine Learning Data Infrastructure
• Cloud Data Platforms
• ETL / ELT Development
• Data Governance & Security
• Distributed Data Processing
• Vector Databases & RAG Systems
• Problem Solving & Analytical Thinking
• Communication & Stakeholder Management
• Ownership & Execution