Job Details

GenAI Data Automation Engineer
100% remote - (Quarterly Travel to Gaithersburg, MD for team activities)
Ability to Obtain Public Trust required
26-01995

Job Summary
The GenAI Data Automation Engineer designs and implements AI-driven automation solutions across AWS and Azure hybrid cloud environments. This role is responsible for building scalable data pipelines, integrating enterprise systems, and leveraging Generative AI frameworks to support mission-critical analytics, reporting, and customer engagement platforms. The position requires strong expertise in data engineering, cloud services, and LLM-based automation, with a focus on performance, security, and compliance in regulated environments.

Job Responsibilities

• Design, develop, and maintain data pipelines using AWS services including S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB, and Step Functions.
• Build ETL/ELT processes to move data across systems, including DynamoDB to SQL Server and AWS to Azure SQL integrations.
• Integrate contact center and CRM data into enterprise data platforms for analytics and operational reporting.
• Engineer and enhance real-time and batch ingestion pipelines using Apache Spark, Flume, and Kafka, delivering data to Solr and OpenSearch platforms.
• Leverage Generative AI frameworks such as AWS Bedrock, Amazon Q, Azure OpenAI, Hugging Face, and LangChain to:
  
  • Automate vector generation and embedding from unstructured data.
  • Implement automated data quality checks, metadata tagging, and lineage tracking.
  • Enhance ETL processes with LLM-assisted transformations and anomaly detection.
  • Build conversational business intelligence interfaces for natural language querying of structured and indexed data.
  • Develop AI-enabled copilots for pipeline monitoring and automated troubleshooting.
• Optimize SQL Server performance through stored procedures, indexing strategies, query tuning, and execution plan analysis.
• Implement CI/CD pipelines using GitHub, Jenkins, or Azure DevOps to support data and AI solution deployment.
• Ensure security and compliance using IAM, encryption, VPC configurations, role-based access controls, and firewall policies.
• Participate in Agile DevOps processes and deliver sprint-based enhancements to data and AI solutions.

• Bachelor degree in Computer Science or related field.
• Minimum of 2 years of experience in data engineering and automation.
• Hands-on experience with LLM and Generative AI frameworks, including AWS Bedrock, Azure OpenAI, or open-source platforms.
• Proficiency in SQL, SSIS, Python, Spark, Bash, PowerShell, and AWS/Azure CLI tools.
• Experience with AWS services such as S3, RDS/SQL Server, Glue, Lambda, EMR, and DynamoDB.
• Familiarity with Apache Flume, Kafka, and Solr for large-scale ingestion and search.
• Experience integrating REST APIs into data pipelines and workflows.
• Knowledge of SDLC and CI/CD tools such as JIRA, GitHub, Azure DevOps, and Jenkins.
• Strong troubleshooting and performance optimization skills in SQL, Spark, or related technologies.
• Experience operationalizing Generative AI pipelines, including deployment, monitoring, retraining, and lifecycle management.
• Strong written and verbal communication skills.
• US Citizenship and ability to obtain Public Trust clearance.
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