AWS Cloud Platform Engineer (AI/ML)

Role: AWS Cloud & AI Platform Engineer II

Location: Cincinnati, OH 45202 – Onsite

Contract: Contract-to-Hire after 6 months

******** Important note: Only candidates who are interested in and eligible to convert to FTE after the contract period encouraged to apply

Position Overview

We are seeking an experienced AWS Cloud & AI Platform Engineer II to help build, enable, and support enterprise AI, Machine Learning, and Generative AI platforms within a secure, scalable, and governed AWS environment.

The ideal candidate will have a strong combination of AWS Cloud/Platform Engineering, Generative AI/LLM technologies, Infrastructure as Code, DevOps, and AI governance/risk management experience.

This role will collaborate closely with engineering, infrastructure, security, risk, data, and business teams to develop reusable AI platform capabilities that meet enterprise security, regulatory, operational, and technology standards.

Key Responsibilities

AI Platform Engineering

• Design, implement, and support secure and scalable AI/GenAI platform solutions.
• Build reusable frameworks, services, architectural patterns, and enablement environments.
• Design and maintain AWS 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 deployments.
• 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 for enterprise AI services.

Generative AI & AI/ML

• Implement and support Generative AI and LLM solutions.
• Work with:
• Prompt Engineering
• RAG
• LLM/model orchestration
• AI evaluation frameworks
• Tool integration
• Agentic AI
• Utilize frameworks such as LangChain and LlamaIndex.
• Support MCPs, vector databases, and enterprise AI integration architectures.
• Support model lifecycle management, observability, monitoring, and evaluation.
• Contribute to responsible, secure, and governed AI adoption.

AWS Cloud & DevOps

• Provision, configure, automate, monitor, and support AWS environments.
• Implement infrastructure using Terraform, CloudFormation, or similar IaC technologies.
• Develop and maintain CI/CD pipelines and DevOps automation.
• Work extensively with AWS services including:
• IAM
• CloudWatch
• S3
• Lambda
• API Gateway
• Bedrock
• SageMaker
• Design scalable, resilient, secure, and operationally efficient cloud environments.

Collaboration & Technical Leadership

• Partner with engineering, infrastructure, security, risk, data, and business teams.
• Lead technical evaluations and proof-of-concept initiatives for emerging technologies.
• Develop architecture documentation, technical standards, operational procedures, and governance artifacts.
• Collaborate with Agile squads and platform engineering teams.
• 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 a related technical field.
• 9+ years of overall technology experience in cloud platform engineering, AI/ML enablement, platform architecture, or enterprise technology delivery.
• Strong hands-on experience with AWS Cloud and AI/ML technologies.
• Experience supporting and operationalizing Generative AI / AI/ML platforms.
• Strong experience with cloud infrastructure automation, DevOps, and IaC.
• Experience working with enterprise security, risk, infrastructure, data, and business teams.

Must-Have Technical Skills

• AWS Cloud
• Generative AI / AI/ML
• AI Risk Management
• 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 & Compliance