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Capstone IT Staffing

Location:
United States, Omaha

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

150000.00 - 165000.00 USD / Year

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Job Description:

This role focuses on designing, developing, and deploying Generative AI and ML applications using AWS SageMaker, Bedrock, and related AWS services. The ideal candidate combines data science and full-stack engineering expertise with a product-oriented mindset, contributing to AI-driven solutions that enhance enterprise capabilities and customer experiences.

Job Responsibility:

Design, build, and integrate Generative AI features into enterprise-scale applications
Develop end-to-end full-stack solutions using Python, Flask, and React, integrating front-end, back-end, and data workflows
Implement and manage AI/ML models using AWS SageMaker and Bedrock, ensuring scalable, secure, and performant deployment
Collaborate closely with product managers, data scientists, and cloud engineers to deliver AI solutions aligned with business needs
Apply prompt engineering and A/B testing techniques to improve AI model reliability and output quality
Maintain and enhance CI/CD processes supporting AI-enabled applications
Stay current with advancements in Generative AI, cloud technologies, and AWS ecosystem tools to inform continuous improvement

Requirements:

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience)
5+ years of experience in full-stack application development within enterprise environments
Hands-on experience building and deploying Generative AI or ML-based applications
Proficiency in Python, React, and Flask for scalable application development
Strong knowledge of AWS services, including SageMaker, Bedrock, Lambda, and related AI tools
Understanding of cloud-native development, API integration, and secure software design principles
Proven ability to collaborate effectively in cross-functional teams and agile environments

Nice to have:

Master’s degree in a technical or analytical discipline
Experience integrating AI/ML APIs or LLM-based systems into production environments
Familiarity with data pipelines, prompt engineering, and AI model monitoring
Exposure to agentic AI architectures or multi-cloud AI deployment strategies

Additional Information:

Job Posted:
December 07, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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