AWS AI Engineer

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.
• Strong understanding of secure AI deployment patterns, IAM, networking, and governed access to AI services.
• Familiarity with model lifecycle management, experimentation, and production AI operations.
• Strong 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 Professional

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.