Role & responsibilities

Job Summary:

Required Skills and Experience
Hands-on experience with Amazon Bedrock and Amazon SageMaker.
Proven ability to deploy, manage, and optimize LLMs and foundation model use cases in AWS.
Strong experience with MLOps practices in SageMaker, including pipelines, model deployment, monitoring, and governance.
Experience building, testing, and validating AI/ML solutions in cloud environments.
Solid understanding of secure AI deployment patterns, IAM, networking, and governed access to AI services.
Familiarity with model lifecycle management, experimentation, and production AI operations.
Robust problem-solving skills and ability to work independently in a contractor capacity.

Preferred Qualifications / Certifications




Relevant AWS certifications preferred, such as:

oAWS Certified Generative AI Developer Qualified

oAWS Certified Machine Learning Engineer – Associate

oAWS Certified Machine Learning – Specialty

oAWS Certified AI Practitioner
Experience with prompt engineering, model evaluation, and AI application integration.
Exposure to responsible AI, model observability, and deployment validation practices.
Familiarity with automation and infrastructure-as-code for AWS AI environments.
Familiarity with FinOps principles and usage in AI workloads.

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