AWS AI Engineer

Hudson Manpower seeks an experienced AWS AI Engineer to design and deploy AI and ML applications on AWS. The role emphasizes retrieval augmented generation systems, LLM fine tuning, and AWS native microservices in a remote US setting.

Responsibilities

• Hands-on work with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate cloud-based AI solutions.
• Lead the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
• Develop and integrate LLM based applications including Retrieval-Augmented Generation (RAG) using LangChain and other frameworks.
• Design cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
• Collaborate with internal stakeholders to translate business objectives 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 and ML operations.
• Create and maintain technical documentation for the team and internal customers.
• Ensure clear and effective communication in English, both written and verbal.

Requirements

• Seven years of hands-on software engineering experience with a strong focus on Python.
• Experience with AWS services, with emphasis on 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 such as SCP and AWS Config.
• Strong background in implementing RAG architectures and using LangChain.
• Proven experience in Infrastructure as Code practices and building Terraform modules for AWS cloud.
• Solid experience with Git-based version control, code reviews, and DevOps workflows.
• Proven track record delivering production ready software with release pipeline integration.

Technologies

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

Benefits

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

Top Skills

• Must Have AWS services including Bedrock, SageMaker, ECS, and Lambda
• Experience with AWS organizations and policy guardrails (SCP, AWS Config)
• Experience implementing RAG architectures and using ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Infrastructure as Code best practices and building Terraform modules for AWS cloud
• Fine-tuning large language models, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows
• Nice to have AWS or relevant cloud certifications
• Nice to have data privacy and compliance best practices (PII handling, secure model deployment)
• Nice to have data science background or experience with structured/unstructured data
• Nice to have exposure to FinOps and cloud cost optimization
• Nice to have Hugging Face, Node.js
• Nice to have Policy as Code development (Terraform Sentinel)

Supervisory Responsibilities

None

Minimum Knowledge, Skills, and Abilities Required

• 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).
• Strong experience implementing RAG architectures and 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.

What You’ll Get

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