AWS AI Engineer

Hudson Manpower is seeking a senior AWS AI Engineer to drive production AI and ML initiatives on AWS from Waukesha, Wisconsin, with remote work options. The role centers on building scalable AI/ML applications, emphasizing retrieval-augmented generation, fine-tuning large language models, and crafting cloud-native microservices that align with business goals.

Responsibilities

• Direct, hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
• Implement AWS cloud services across infrastructure, machine learning, and AI platform services.
• Develop LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks.
• Build 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 systems.
• Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code (Terraform).
• Support the development and evolution of reusable platform components for AI/ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Exhibit excellent verbal and written communication skills in English.

Requirements

• At least seven years of hands-on software engineering experience with a strong focus on Python.
• Experience with AWS services, especially Bedrock or SageMaker.
• Familiarity 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 using LangChain.
• Experience in Infrastructure as Code best practices and building Terraform modules for AWS cloud.
• Strong background in Git-based version control, code reviews, and DevOps workflows.
• Proven success delivering production-ready software with release pipeline integration.

Technologies

• Python, Bedrock, SageMaker, ECS, Lambda, Step Functions, DynamoDB, S3
• LangChain, Transformers, PyTorch, TensorFlow
• Terraform, Terraform Sentinel, Git, GitHub
• Hugging Face, Node.js, Golang

Top Skills

• Must Have
  • AWS services - Bedrock, SageMaker, ECS and Lambda
  • Demonstrated experience with AWS Organizations and policy guardrails (SCP, AWS Config)
  • Experience implementing RAG architectures and using ML tooling like Transformers, PyTorch, TensorFlow, and LangChain
  • Infrastructure as Code best practices and building Terraform modules for AWS
  • Fine-tuning large language models, building datasets, and deploying ML models to production
  • Git-based version control, code reviews, and DevOps workflows
  • Proven ability to deliver production-ready software with release pipeline integration
• Nice To Have
  • AWS or relevant cloud certifications
  • Policy as Code development (Terraform Sentinel)
  • Experience with Hugging Face, Golang, or Node.js
  • Exposure to FinOps and cloud cost optimization
  • Data science background or experience with structured/unstructured data
  • Awareness of data privacy and compliance best practices (PII handling, secure model deployment)

Benefits

• Competitive base salary
• Medical, dental, and vision insurance coverage
• Optional life and disability insurance provided
• 401(k) with a company match and optional profit sharing
• Paid vacation time
• Paid Bench time
• Training allowance offering
• Referral bonuses