GenAI Data Automation Engineer

GenAI Data Automation Engineer

Department: IT / Data Engineering / Artificial Intelligence

Location – Remote (Quarterly Travel to Gaithersburg, MD for team activities)

Role Type: Contract (W2) – 6 months with possibility of extension

About Our Client

Our client is a long-established, mission-driven technology and engineering organization that supports critical federal and highly regulated programs across the United States. With decades of experience delivering complex IT, data, and analytics solutions, the organization partners closely with government agencies to modernize systems, improve operational efficiency, and enable data-driven decision-making. They operate nationwide, employ tens of thousands of professionals, and are known for combining deep technical expertise with a strong public-service mission focused on trust, integrity, and measurable impact.

Job Description

The GenAI Data Automation Engineer will design, build, and enhance AI-driven data automation solutions within hybrid AWS and Azure cloud environments. This role focuses on creating scalable, secure data pipelines that integrate enterprise systems, cloud services, and Generative AI capabilities to support analytics, reporting, and customer engagement platforms.

On a day-to-day basis, this engineer will work hands-on with cloud-native data services, real-time and batch ingestion frameworks, and modern Generative AI tools to automate data processing, improve data quality, and enable intelligent insights. The role collaborates closely with data engineers, DevOps teams, and government stakeholders to deliver reliable, production-ready solutions in an Agile environment.

The ideal candidate is delivery-focused, mission-oriented, and enjoys solving complex technical problems through automation, data engineering, and applied Generative AI.

Duties and Responsibilities

• Design and maintain scalable data pipelines in AWS using services such as S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB, and Step Functions.
• Develop ETL/ELT processes to move data across multiple platforms, including AWS and Azure SQL environments.
• Integrate CRM and contact-center data sources into enterprise data pipelines for analytics and reporting.
• Engineer real-time and batch ingestion pipelines using Apache Spark, Kafka, and Flume.
• Implement search and analytics ingestion into platforms such as Apache Solr and AWS OpenSearch.
• Leverage Generative AI frameworks to automate vector creation, embeddings, and unstructured data processing.
• Build AI-assisted data quality checks, metadata tagging, and lineage tracking solutions.
• Enhance ETL workflows using LLM-assisted transformations and anomaly detection.
• Develop conversational analytics and natural-language query interfaces for data access.
• Create AI-powered monitoring and troubleshooting tools for data pipelines.
• Optimize SQL Server performance through stored procedures, indexing, and query tuning.
• Implement CI/CD pipelines using GitHub, Jenkins, or Azure DevOps.
• Ensure security and compliance through IAM, encryption, RBAC, and network controls.
• Support Agile delivery through sprint-based development and cross-team collaboration.

Required Experience / Skills

• Bachelor’s degree in Computer Science or a related field.
• 2+ years of hands-on experience in data engineering, automation, or related roles.
• Hands-on experience with Generative AI or LLM frameworks (AWS Bedrock, Azure OpenAI, Hugging Face, LangChain).
• Strong experience with SQL, Python, Spark, Bash, PowerShell, and cloud CLIs.
• Experience working with AWS services such as S3, RDS/SQL Server, Glue, Lambda, EMR, and DynamoDB.
• Familiarity with Apache Kafka, Flume, and Solr for large-scale ingestion and search.
• Experience integrating REST APIs into data pipelines and workflows.
• Experience with CI/CD tools and Agile SDLC processes.
• Strong troubleshooting and performance optimization skills.
• Excellent communication and collaboration skills.
• U.S. Citizenship and ability to obtain a Public Trust clearance.

Nice-to-Haves

• Experience operating and monitoring GenAI or LLM pipelines in production (GenAI Ops).
• Experience with hybrid AWS/Azure architectures.
• Prior experience supporting federal or highly regulated environments.
• Familiarity with JIRA for Agile project tracking.

Education

Bachelor’s degree in Computer Science or a related technical discipline required.
 

Pay & Benefits Summary

Pay Rate: $50/hour (W2)

Call to Action

Apply now to work on cutting-edge Generative AI and data automation solutions supporting mission-critical federal programs.

GenAI | Data Engineering | AWS | Azure | Generative AI | Python | SQL | Spark | CI/CD | Cloud Automation | Public Trust