Technology Specialist

Job Summary

Serve as a technology specialist focused on generative artificial intelligence and advanced analytics using AWS Bedrock image and text Amazon Sagemaker and Amazon Athena in a hybrid work model. Apply eight to twelve years of hands on experience to design implement and optimize secure scalable solutions that improve business decisions and deliver responsible innovation for global stakeholders.

Responsibilities

• Design and implement robust generative artificial intelligence solutions that use AWS Bedrock image and text to address complex business challenges and create measurable value for global initiatives.
• Architect scalable machine learning workflows on Amazon Sagemaker that streamline model development training deployment and monitoring while improving reliability and performance for production systems.
• Develop and optimize data query strategies on Amazon Athena that enable fast cost efficient analytics and empower business teams to derive timely insights from diverse structured and semi structured data sources.
• Collaborate with product data and engineering teams to translate strategic requirements into practical cloud native designs that align with enterprise standards and deliver clear outcomes for internal and external customers.
• Implement strong security and compliance controls across AWS Bedrock Amazon Sagemaker and Amazon Athena solutions to protect sensitive data and adhere to organizational guidelines and regional regulations.
• Evaluate new generative artificial intelligence features within AWS Bedrock image and text and provide recommendations on adoption that improve solution quality explainability and responsible use across business functions.
• Optimize resource usage and cost models for Sagemaker training jobs Bedrock inference endpoints and Athena queries to ensure efficient cloud spending and predictable performance for critical workloads.
• Provide detailed technical guidance and documentation that describe solution architectures configuration choices and operational procedures to support smooth knowledge transfer and long term maintainability.
• Troubleshoot complex issues across data pipelines machine learning models and inference services by performing structured analysis and implementing durable fixes that prevent recurrence and downtime.
• Partner with analytics and domain experts to design experiments and evaluation frameworks that measure the impact of Bedrock and Sagemaker models on key business metrics and societal outcomes.
• Drive continuous improvement by reviewing existing generative artificial intelligence and analytics solutions identifying optimization opportunities and implementing enhancements that raise solution quality and user satisfaction.
• Coordinate effectively in a hybrid work environment by using digital collaboration tools planning on site engagements when required and maintaining strong communication across distributed teams during day shifts.
• Contribute to organizational innovation initiatives by sharing insights on emerging generative artificial intelligence practices using AWS services and demonstrating how responsible technology adoption can benefit communities and customers.

Qualifications

• Demonstrate eight to twelve years of progressive experience in cloud based solution development with deep hands on expertise in AWS Bedrock image and text Amazon Sagemaker and Amazon Athena for production grade implementations.
• Apply strong proficiency in Python or similar programming languages to build machine learning pipelines integrate Bedrock and Sagemaker endpoints and automate data processing tasks for analytics workflows.
• Exhibit solid understanding of AWS core services including compute storage and networking to design secure scalable architectures that support generative artificial intelligence and advanced analytics solutions.
• Utilize experience with data modeling and query optimization to design Athena structures and queries that improve performance reliability and readability for business intelligence and reporting use cases.
• Show practical knowledge of machine learning lifecycle management including feature engineering training evaluation deployment and monitoring with a focus on Sagemaker capabilities and best practices.
• Demonstrate familiarity with responsible artificial intelligence principles including fairness transparency and safety and apply these concepts when designing Bedrock image and text use cases for enterprise environments.
• Bring excellent communication and stakeholder management skills that support collaboration with multidisciplinary teams and enable clear explanation of complex technical topics to non technical audiences.