Job Description
AWS AI Team Lead
SAIC
Ashburn, VA
• On-site, Remote
Full-time
$160K - $200K/yr
Posted 15 hours ago
Job Description
Job ID: 2600149
Location: REMOTE WORK, VA, US
Date Posted: 2026-01-07
• Category: Engineering and Sciences
• Subcategory: Machine Learning Engineer
• Schedule: Full-time
• Shift: Day Job
• Travel: No
• Minimum Clearance Required: None
• Clearance Level Must Be Able to Obtain: Public Trust
• Potential for Remote Work: Yes
We are seeking a Team Lead for the AWS AI & GenAI Solutions Team to oversee the design, development, and delivery of advanced AI/ML and GenAI capabilities within the IRS Advanced Analytics Program (AAP). This role provides technical and delivery leadership for a multi-disciplinary team building scalable, secure, and reusable AI/ML workflows on AWS services such as SageMaker, Bedrock, Lambda, and Step Functions.
The AWS AI Team Lead serves as both a hands-on technical leader and a strategic collaborator, ensuring AAP’s AI/ML and LLM solutions align with enterprise architecture, governance, and mission team requirements. This role partners closely with the Chief Architect, Product Manager, and Databricks Lead to define cross-platform integration patterns and accelerate model development and deployment.
Key Responsibilities
• Lead the AWS AI/LLM engineering team delivering AI/ML and GenAI solutions using SageMaker, Bedrock, and related services.
• Provide technical oversight and hands-on guidance in model development, fine-tuning, deployment, and inference.
• Collaborate with the Databricks, Infra, and Trustworthy AI teams to design cross-platform AI/ML workflows.
• Define standards and reusable patterns for model pipelines, API integrations, and data flow between SageMaker, Bedrock, and Databricks.
• Guide the development of secure, compliant architectures that meet IRS enterprise governance and ATO requirements.
• Mentor AI/ML and LLM engineers, data engineers, and automation testers in technical execution and solution design.
• Partner with Product Management to translate customer needs into technical roadmap items and delivery milestones.
• Ensure quality, cost-efficiency, and performance of AWS AI solutions through consistent monitoring and optimization.
• Support customer demos, workshops, and onboarding sessions as the technical SME for AWS AI/GenAI capabilities.
• Stay current with emerging AWS and GenAI technologies, advising on their adoption and integration.
Qualifications
Required Qualifications:
• Must be a U.S. Citizen with the ability to obtain and maintain a Public Trust security clearance
• Bachelor’s or Master’s degree in Computer Science, AI/ML Engineering, or related technical field.
• 8+ years of experience in AI/ML engineering, data science, or cloud-based model development.
• 3+ years of leadership experience managing or mentoring technical teams.
• Deep hands-on expertise with AWS SageMaker, Bedrock, and AI/ML workflows (training, fine-tuning, deployment, inference).
• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain).
• Working knowledge of AWS cloud services (S3, Lambda, Step Functions, ECS/EKS).
• Familiarity with MLOps concepts and CI/CD integration for AI workflows.
• Experience implementing or integrating Trustworthy AI principles (bias testing, explainability, traceability).
Desired Skills
• Certifications: AWS Certified Machine Learning Specialty, AWS Solutions Architect Professional, or equivalent.
• Understanding of LLM integration patterns (RAG, prompt chaining, multi-model orchestration).
• Familiarity with federal compliance standards (FedRAMP, NIST 800-53) and ATO processes.
• Experience building secure, API-based AI/ML services for enterprise consumption.
• Excellent communication and presentation skills for both executive and technical audiences.
• Ability to manage cross-functional collaboration between engineering, architecture, and customer success teams.
Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
