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AWS Engineer with AI/ML
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What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$122,585 / year median in Kentucky
Job Description
AWS Engineer with AI/ML at Prudent Technologies and Consulting, Inc. AWS Engineer with AI/ML at Prudent Technologies and Consulting, Inc. in Dayton, Kentucky Posted in about 2 hours ago.
Type:
full-time
Role:
AWS Engineer with
AI/ML Location:
Cincinnati, OH 45202 (Onsite)
Job Type :
Contract-to-Hire after 6 months Position Overview We are seeking an experienced AWS Cloud & AI Platform Engineer II to enable and advance enterprise AI and Machine Learning capabilities within a secure, scalable, and governed cloud environment. The engineer will design, implement, and support AWS-based AI/ML and Generative AI platforms , enabling experimentation, proof of concepts, model development, and enterprise adoption of AI solutions. This role will work closely with engineering, infrastructure, security, risk, data, and business teams to build reusable AI platform capabilities aligned with enterprise technology, security, regulatory, and operational standards. Key Responsibilities AI Platform Engineering & Enablement Design, implement, and support secure and scalable AI/GenAI platform capabilities. Build reusable frameworks, services, architectural patterns, and enablement environments. Architect and maintain AWS cloud infrastructure using Infrastructure as Code (IaC) and automation. Support
AWS AI/ML
services including: Amazon Bedrock Amazon SageMaker Amazon S3 AWS Lambda API Gateway Amazon Lex Enable AI/ML experimentation, POCs, and production-ready solutions. Evaluate and operationalize emerging AI/ML and Generative AI technologies. Develop AI platform standards, reference architectures, guardrails, and best practices. Support structured and unstructured data integrations and enterprise AI services. Generative
AI & AI/ML
Enable Generative AI capabilities including: Prompt Engineering RAG Model orchestration AI evaluation frameworks Tool integration Agentic AI Work with frameworks such as LangChain and LlamaIndex . Support MCPs, vector databases, and enterprise AI integration architectures . Support model lifecycle management, observability, monitoring, and AI evaluation. Contribute to responsible and governed AI adoption. AWS Cloud & Platform Engineering Provision, configure, automate, monitor, and support AWS cloud environments. Implement cloud infrastructure using Terraform, CloudFormation, or similar IaC tools . Develop CI/CD pipelines and DevOps automation.
Support AWS services including:
IAM CloudWatch S3 Lambda API Gateway Bedrock SageMaker Design scalable, resilient, and operationally efficient cloud environments. Collaboration & Technical Leadership Partner with engineering, infrastructure, security, risk, data, and business teams. Lead technical exploration and evaluation of emerging technologies. Develop technical documentation, architecture guidance, operational procedures, and governance artifacts. Collaborate with Agile squads and platform engineering teams. Help establish best practices for enterprise AI platform development and deployment. Take ownership of assigned platform initiatives and deliver solutions aligned with business priorities.
Required Qualifications:
Bachelor's degree in computer science, Information Technology, Engineering, Data Science, Mathematics, or related technical field. 12+ years of experience in cloud platform engineering, AI/ML enablement, platform architecture, or enterprise technology delivery. Hands-on experience with AWS cloud platforms and AI/ML technologies . Experience supporting or operationalizing Generative AI and AI/ML platforms . Strong experience with cloud infrastructure automation, DevOps, and IaC. Experience working with enterprise engineering, security, risk, infrastructure, data, and business teams. Must-Have Technical Skills AWS Cloud AI Risk Management Generative
AI / AI/ML
Amazon Bedrock Amazon SageMaker S3, Lambda, API Gateway IAM & CloudWatch Terraform / CloudFormation CI/CD & DevOps Python
SQL REST
APIs / Cloud Integrations RAG Prompt Engineering AI/ML Model Evaluation LangChain / LlamaIndex Vector Databases Agentic
AI MCP AI
governance, security, risk, and compliance
Benefits
- Dental Insurance