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[Remote] GenAI Data Automation Engineer

Work from home Full-time role Hiring

Note: The job is a remote job and is open to candidates in USA. System One is a leader in delivering outsourced services and workforce solutions across North America. They are seeking a GenAI Data Automation Engineer to design and maintain data pipelines in AWS, develop ETL processes, and leverage Generative AI services for data automation and analytics.

Responsibilities

  • Design and maintain data pipelines in AWS using S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB, and Step Functions
  • Develop ETL/ELT processes to move data between DynamoDB, SQL Server (AWS), and Azure SQL systems
  • Integrate AWS Connect CRM data into the enterprise data pipeline for analytics and operational reporting
  • Engineer, enhance ingestion pipelines with Apache Spark, Flume, Kafka for real-time and batch processing into Apache Solr, AWS Open Search platforms
  • Leverage Generative AI services and Frameworks (AWS Bedrock, Amazon Q, Azure OpenAI, Hugging Face, LangChain) to create automated processes for vector generation and embeddings, automate data quality checks, metadata tagging, and lineage tracking, and enhance ingestion/ETL with LLM-assisted transformation and anomaly detection
  • Build conversational BI interfaces that allow natural language access to Solr and SQL data
  • Develop AI-powered copilots for pipeline monitoring and automated troubleshooting
  • Implement SQL Server stored procedures, indexing, query optimization, profiling, and execution plan tuning to maximize performance
  • Apply CI/CD best practices using GitHub, Jenkins, or Azure DevOps for data pipelines and GenAI model integration
  • Ensure security and compliance through IAM, KMS encryption, VPC isolation, RBAC, and firewalls
  • Support Agile DevOps processes with sprint-based delivery of pipeline and AI-enabled features

Skills

  • BS in Computer Science or related field with 2+ years of data engineering, automation experiences
  • Hands-on experience with SQL, SSIS, Python, Spark, Bash, PowerShell, AWS/Azure CLIs
  • Experience with AWS services like S3, RDS/SQL Server, Glue, Lambda, EMR, DynamoDB
  • Familiarity with Apache Flume, Kafka, Solr for large-scale data ingestion and search
  • Familiarity with LLM, Gen AI frameworks using AWS Bedrock, Azure OpenAI or open source platforms and tools
  • Experience with integrating REST API calls in workflows
  • Familiarity with JIRA, GitHub / Azure DevOps / Jenkins for SDLC and CI/CD automation
  • Strong troubleshooting and performance optimization skills in SQL, Spark or other data solutions
  • Experience operationalizing Generative AI (GenAI Ops) pipelines, including model deployment, monitoring, retraining, and lifecycle management for LLMs and AI-enabled data workflows
  • Good communication and presentation skills
  • Ability to obtain Federal government Public Trust clearance
  • Certifications: AWS Data Engineer, AWS AI/ML Specialty, Azure AI Engineer, Databricks Data Engineer
  • Experience implementing RAG pipelines, embeddings, and vector search with Solr, OpenSearch, FAISS, Pinecone, or Pgvector/SQL server vector types
  • Experience with GenAI powered coding tools such as Claude Code, OpenAI Codex, VS Code
  • Experience with multi-cloud data integration (AWS – Azure SQL)
  • Familiarity with Microsoft BizTalk and SSIS for SQL Server ETL workflows
  • Knowledge of data lineage/governance tools (Purview, Unity Catalog, AWS Glue Catalog)
  • Familiarity with Infrastructure-as-Code (Terraform/CloudFormation, Bicep) for deployments
  • Experience with compliance frameworks (FedRAMP, PCI-DSS, HIPAA)

Benefits

  • Health and welfare benefits coverage options including medical, dental, vision, spending accounts, life insurance, voluntary plans, as well as participation in a 401(k) plan

Company Overview

  • System One is a professional staffing firms. It was founded in 2008, and is headquartered in Pittsburgh, Pennsylvania, USA, with a workforce of 5001-10000 employees. Its website is http://www.systemoneservices.com.
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