AI Data Engineer

United StatesRemoteFull-timemid

OtherAi Data Engineer

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Data Engineer based in United States. As an AI Data Engineer,

Technical Tools

OtherAi Data Engineer

As an AI Data Engineer, you will design, build, and maintain modern data pipelines, AI solutions, and analytics platforms that support complex operational and analytical needs. You will combine data engineering expertise with practical knowledge of AI, machine learning, prompt engineering, agentic AI, and retrieval-augmented generation. The role spans data architecture, ETL development, cloud technologies, APIs, DevOps, and production reliability. You will collaborate with database administrators, application developers, and cross-functional teams to deliver scalable and high-quality solutions. Working in an Agile environment, you will also contribute to automation, documentation, troubleshooting, and continuous improvement. This contract opportunity is suited to an experienced engineer who can work independently while navigating technically complex and evolving requirements.

Design, develop, test, and maintain data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources.
Build and optimize data architectures and models that support analytics, reporting, and operational requirements.
Develop AI-enabled solutions using concepts such as prompt engineering, machine learning, agentic AI, and retrieval-augmented generation (RAG).
Implement and manage CI/CD pipelines for data engineering workflows using Git and related development tools.
Develop and deploy cloud-based solutions using Azure Functions and containerization technologies such as Docker and Kubernetes.
Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs.
Develop and support RESTful and SOAP APIs and integrate data and AI/ML components into broader applications.
Ensure data quality and integrity through validation, monitoring, logging, and proactive issue resolution.
Troubleshoot and resolve production issues while maintaining high availability and reliability of data solutions.
Manage multiple tasks and competing priorities while delivering projects within an Agile development environment.
Document data flows, processes, architectures, and technical solutions to support knowledge sharing and compliance.
Present project status, technical work products, and complex concepts to technical and non-technical stakeholders.
Stay current with emerging technologies and best practices across data engineering, AI, cloud, and DevOps.

Requirements

~2 min read

Bachelor’s degree required.
5+ years of experience in data engineering, software development, or a related technical discipline.
Must be able to obtain and maintain a Public Trust.
Hands-on experience with AI methods and tools, including prompt engineering, machine learning, agentic AI, RAG, and tools such as Copilot and Codex.
Strong programming experience with Java, Python, SQL, and PySpark.
Experience designing and developing scalable data pipelines and ETL processes.
Extensive experience with relational and NoSQL databases, including MySQL, PostgreSQL, SQL Server, and MongoDB, as well as stored procedure development.
Experience working with Databricks.
Experience developing and managing CI/CD pipelines using tools such as GitHub.
Familiarity with Git, Azure DevOps, and modern version control and collaboration practices.
Experience working in Agile development environments.
Experience with API development, including RESTful and SOAP services.
Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.
Ability to work independently and manage multiple priorities in a fast-paced environment.
Familiarity with security best practices and compliance requirements in federal environments is preferred.
Experience with microservices, Spring Boot, and AI/ML component integration is advantageous.
Experience supporting federal programs or large-scale data modernization initiatives is a plus.
Previous consulting experience is preferred.