AWS AI Engineer

Hudson Manpower is seeking a Senior AWS AI Engineer to design and deploy production AI and ML applications on AWS, with a focus on retrieval-augmented generation, fine-tuning large language models, and AWS-native microservices. This role is based in Redmond, Washington, with remote work options, and combines hands-on cloud engineering with advanced ML deployment to deliver scalable, secure AI solutions.

Responsibilities

• Engage hands-on with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate production workflows.
• Lead the design and implementation of AWS cloud infrastructure and AI platform services, spanning infrastructure, ML pipelines, and AI tooling.
• Develop LLM-based applications, including Retrieval-Augmented Generation (RAG) solutions using LangChain and alternative 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 systems.
• 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/ML operations.
• Produce and maintain technical documentation for the team and internal customers.
• Demonstrate excellent verbal and written communication skills in English.

Requirements

• Minimum of 7 years of hands-on software engineering experience with a strong emphasis on Python.
• Proficiency with AWS services, particularly Bedrock or SageMaker.
• Experience fine-tuning large language models or building datasets and deploying ML models to production.
• Solid experience with AWS Organizations and policy guardrails such as SCP and AWS Config.
• Demonstrated expertise in implementing RAG architectures and using LangChain.
• Strong background in Infrastructure as Code best practices and building Terraform modules for AWS.
• Proven ability with Git-based version control, code reviews, and DevOps workflows.
• Track record delivering production-ready software with integrated release pipelines.

Technologies

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

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
• Referral bonuses

Top Skills

• Proficiency with AWS services including Bedrock, SageMaker, ECS, and Lambda
• Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Hands-on experience implementing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Breadth in Infrastructure as Code and building Terraform modules for AWS
• Fine-tuning LLMs, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows

Nice to Have

• AWS or other cloud certifications
• Data privacy and compliance practices (PII handling, secure model deployment)
• Data science background or experience with structured and unstructured data
• Exposure to FinOps and cloud cost optimization
• Experience with Hugging Face, Node.js
• Policy as Code development (e.g., Terraform Sentinel)