GenAI Data Automation Engineer

Job Title: GenAI Data Automation Engineer

Location: Washington, DC (Remote)

Type: Contract To Hire

Compensation: $48.95 /hr

Security Clearance: Public Trust

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.
• Requirements:
• 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.
• Preferred (plus)
• 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).
• System One, and its subsidiaries including Joulé and Mountain Ltd., are leaders in delivering outsourced services and workforce solutions across North America. We help clients get work done more efficiently and economically, without compromising quality. System One not only serves as a valued partner for our clients, but we offer eligible employees 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.
• System One is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, age, national origin, disability, family care or medical leave status, genetic information, veteran status, marital status, or any other characteristic protected by applicable federal, state, or local law.
• #M-M2

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