AI/ML Data Engineer at SAIC

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Full Time

Start Date

Immediate

Expiry Date

08 Jan, 26

Salary

0.0

Posted On

10 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AWS, Data Engineering, AI/ML, LLM, Python, SQL, Data Transformation, Feature Engineering, CI/CD, Terraform, CloudFormation, Data Validation, Schema Enforcement, MLOps, Security, Governance

Industry

Defense and Space Manufacturing

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. Required Qualifications Bachelor’s degree at 9 years or more years of experience; Masters degree at 6 years or more experience in computer science, Data Engineering, or related field. Experience in 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.

Responsibilities

The Data Engineer will design, build, and optimize data pipelines in AWS to support AI/ML and LLM workloads. They will collaborate with mission data scientists to ensure datasets are structured and optimized for model development and deployment.