AWS AI Engineer

Hudson Manpower is seeking an experienced AWS AI Engineer in Cincinnati with remote options. The role centers on building retrieval-augmented generation systems, fine-tuning large language models, and delivering AWS-native microservices to support automation and governance in an enterprise environment. This position prioritizes practical cloud engineering, secure architectures, clear collaboration, and scalable AI capabilities.

Benefits

• Competitive base salary
• Medical, dental, and vision insurance coverage
• Optional life and disability insurance
• 401(k) with company match and optional profit sharing
• Paid vacation time
• Paid bench time
• Training allowance offered
• Eligibility to earn referral bonuses

Responsibilities

• Hands on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build scalable AI systems
• Implement and manage AWS cloud services across infrastructure, machine learning, and AI platform components
• Develop LLM based applications, implementing Retrieval-Augmented Generation (RAG) with LangChain and similar frameworks
• Create cloud native microservices, APIs, and serverless functions to enable intelligent automation and real time data processing
• Collaborate with internal stakeholders to translate business goals into secure, scalable AI solutions
• Own the software release lifecycle, including CI/CD pipelines, GitHub based SDLC, and infrastructure as code with Terraform
• Support the development and evolution of reusable platform components for AI and ML operations
• Create and maintain technical documentation for the team and internal customers
• Excellent verbal and written communication skills in English

Requirements

• 7 years of hands-on software engineering experience with a strong focus on Python
• Experience with AWS services, especially Bedrock or SageMaker
• Familiar with fine tuning large language models or building datasets and deploying ML models to production
• Demonstrated experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Solid experience implementing RAG architectures and LangChain
• Experience with infrastructure as code best practices and building Terraform modules for AWS
• Strong background in Git based version control, code reviews, and DevOps workflows
• Demonstrated success delivering production ready software with release pipeline integration

Technologies

• Python
• Bedrock
• SageMaker
• Lambda
• ECS
• Step Functions
• DynamoDB
• S3
• LangChain
• Transformers
• PyTorch
• TensorFlow
• Terraform
• Git
• GitHub
• Hugging Face
• Node.js
• Terraform Sentinel
• AWS Config
• AWS Organizations
• SCP

Supervisory responsibilities

None