**Description** We are seeking a **Data Engineer with hands-on AI/ML and LLM project experience in AWS** to join the AWS AI/GenAI Solutions Team within the IRS Advanced Analytics Program (AAP). This role is responsible for designing and maintaining **data pipelines and feature engineering workflows** that directly enable **LLM/GenAI and AI/ML model development, training, and deployment** on AWS services such as SageMaker and Bedrock. As part of the AAP common services mission, the Data Engineer will deliver **secure, scalable, and reusable AWS-native data engineering solutions** that simplify onboarding for IRS mission teams. The ideal candidate combines expertise in **AWS data services** with **AI/ML-focused engineering** to ensure mission teams can build and operationalize models efficiently. **Key Responsibilities** + Design, build, and optimize **data pipelines in AWS** (Glue, Lambda, Step Functions, S3, RDS, Redshift) to support AI/ML and LLM workloads. + Implement **data ingestion, transformation, and feature engineering workflows** that feed SageMaker and Bedrock models. + Collaborate with mission data scientists to ensure **datasets are structured and optimized** for LLM fine-tuning, inference, and prompt engineering. + Integrate pipelines into **CI/CD workflows** for automated, repeatable, and compliant model operations. + Apply **security and governance controls** (IAM roles, encryption, audit logging) to protect sensitive IRS data. + Develop and maintain **data validation, schema enforcement, and monitoring routines** to ensure reliability and compliance. + Work with MLOps/SRE engineers to align pipelines with **model lifecycle operations** (staging, promotion, retraining). + Partner with Product Manager and Chief Architect to align AWS data engineering capabilities with AAP roadmap milestones. **Qualifications** **Required Qualifications** + Bachelor’s degree in computer science, Data Engineering, or related field. + 10+ years of **data engineering experience on AWS** , including **AI/ML-focused use cases** . + Hands-on expertise with **AWS data services** (Glue, Lambda, S3, Redshift, RDS, Step Functions). + Strong proficiency in **Python, SQL, and data transformation frameworks** . + Experience delivering **feature engineering and data prep** for SageMaker/Bedrock model development. + Familiarity with **CI/CD integration** and IaC (Terraform, CloudFormation). + Awareness of **AI/ML lifecycle data needs** (training, fine-tuning, inference, retraining). **Desired Skills** + Certifications: **AWS Certified Data Analytics Specialty, AWS Certified Machine Learning Specialty, or Solutions Architect Associate/Professional** . + Experience working with **LLM-specific pipelines** (prompt data preparation, response validation, fine-tuning datasets). + Familiarity with **federal compliance frameworks** (FedRAMP, NIST 800-53) and embedding compliance into AWS data workflows. + Exposure to **Trustworthy AI practices** (bias detection, data lineage, explainability). + Strong collaboration skills to work across architects, AI/LLM engineers, and mission data scientists. Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors. REQNUMBER: 2510286 SAIC is a premier technology integrator, solving our nation's most complex modernization and systems engineering challenges across the defense, space, federal civilian, and intelligence markets. Our robust portfolio of offerings includes high-end solutions in systems engineering and integration; enterprise IT, including cloud services; cyber; software; advanced analytics and simulation; and training. We are a team of 23,000 strong driven by mission, united purpose, and inspired by opportunity. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $6.5 billion. For more information, visit saic.com. For information on the benefits SAIC offers, see Working at SAIC. EOE AA M/F/Vet/Disability