GenAI Data Automation Engineer

Leidos is seeking a GenAI Data Automation Engineer to design and implement innovative, AI-driven automation solutions across AWS and Azure hybrid environments. You will be responsible for building intelligent, scalable data pipelines and automations that integrate cloud services, enterprise tools, and Generative AI to support mission-critical analytics, reporting, and customer engagement platforms. Ideal candidate is mission focused, delivery oriented, applies critical thinking to create innovative functions and solve technical issues.

Who we are

Leidos is a Fortune 500® technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, civil, and health markets.  Leidos Civil Group helps the government modernize operations with leading edge AI/ML driven data management and analytics solutions.  We are trusted partners to both government and highly regulated commercial customers looking for transformative solutions in mission IT, security, software, engineering, and operations. We work with our customers including the FAA, DOE, DOJ, NASA, National Science Foundation, Transportation Security Administration, Custom and Border Protection, airports, and electric utilities to make the world safer, healthier, and more efficient.

In this role, you will:

• 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 from multiple data systems including DynamoDB → SQL Server (AWS) and between AWS ↔ Azure SQL systems.
• Integrate AWS Connect, Nice inContact 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 embedding from unstructured data to support Generative AI models.
  • Automate data quality checks, metadata tagging, and lineage tracking.
  • 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 both 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.

Required Qualifications:

• BS in Computer Science or related field with 2+ years of data engineering, automation experiences.
• Hands-on experience with LLM, Generative AI frameworks using AWS Bedrock, Azure OpenAI or open source platform.
• Hands-on experience with SQL, SSIS, Python, Spark, Bash, Power shell, 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.
• Experience with integrating REST API calls in data pipelines and 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 engineering 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.
• US Citizenship and ability to obtain Public Trust clearance.

Preferred (plus):

• Certifications: AWS Data Engineer, AWS AI/ML Specialty, Azure AI Engineer, Databricks certified Data Engineer.
• Experience implementing RAG pipelines, embeddings, and vector search with Solr, OpenSearch, FAISS, Pinecone, or Pgvector.
• 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 automated deployments.
• Experience with compliance frameworks (FedRAMP, PCI-DSS, HIPAA).

Come break things (in a good way). Then build them smarter.

We're the tech company everyone calls when things get weird. We don’t wear capes (they’re a safety hazard), but we do solve high-stakes problems with code, caffeine, and a healthy disregard for “how it’s always been done.”

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.