AWS AI Engineer

Hudson Manpower; Wilmington (NC); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive base salary

Medical, dental, and vision insurance

401(k) with company match and profit‑/

Paid vacation

Training allowance

Referral bonuses

Job summary

Hudson Manpower seeks a Senior AI and AWS engineer to deliver production-grade AI/ML capabilities on AWS, including RAG systems, LLM fine-tuning, and cloud-native microservices in an enterprise setting.

You will work hands-on with AWS services like Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3, and own the release lifecycle with Terraform IaC, while collaborating with stakeholders to translate business goals into secure, scalable AI platforms.

Qualifications

• 7+ years hands-on software engineering with Python.
• Experience with AWS services, especially Bedrock or SageMaker.
• Familiarity with fine-tuning LLMs and deploying ML models to production.
• Experience with AWS Organizations and policy guardrails (SCP, AWS Config).
• Knowledge of RAG architectures and LangChain.

Responsibilities

• Design and build AI/ML cloud applications on AWS.
• Develop RAG systems and fine-tuned LLMs for production use.
• Create cloud-native microservices and serverless components.
• Own release lifecycle, CI/CD pipelines, and Terraform IaC.
• Draft reusable AI/ML platform components and technical docs.

Skills

Python

AWS Bedrock/SageMaker

LLM fine-tuning

LangChain

Terraform

Git/GitHub DevOps

AWS Lambda/ECS

Tools

Terraform

LangChain

Hugging Face

PyTorch

TensorFlow

SageMaker

Bedrock

Job description

Senior AI and AWS engineer focused on delivering production-grade AI/ML capabilities on AWS, including retrieval-augmented generation, LLM fine-tuning, and cloud-native microservices in an enterprise setting.

Responsibilities

• Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3
• Design and implement AWS cloud services spanning infrastructure, machine learning, and AI platform tooling
• 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 with 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

• 7 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 LangChain
• Experience in Infrastructure as Code best practices and building Terraform modules for AWS
• 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
• GitHub
• Hugging Face
• Node.js
• Golang
• AWS Config
• SCP
• AWS Organizations

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
• Referral bonuses

Top Skills

• AWS services including Bedrock, SageMaker, ECS, and Lambda
• Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
• Proficiency in RAG architectures and ML tooling such as Transformers, PyTorch, TensorFlow, and LangChain
• Infrastructure as Code practices and Terraform module development for AWS
• Fine‑tuning LLMs, building datasets, and deploying ML models to production
• Git-based version control, code reviews, and DevOps workflows
• AWS or relevant cloud certifications
• Data privacy and compliance best practices (PII handling, secure model deployment)
• Data science background or experience with structured and unstructured data
• Exposure to FinOps and cloud cost optimization
• Hugging Face, Node.js
• Policy as Code development (Terraform Sentinel)

What you'll do

• Design, build, and operate AI/ML applications in the cloud with real infrastructure, data, and users
• Develop retrieval‑augmented generation systems and fine‑tuned LLMs for production use
• Create cloud‑native microservices and serverless components to support automation and real‑time processing
• Collaborate with stakeholders to convert business needs into secure, scalable AI solutions
• Own the release lifecycle, CI/CD pipelines, GitHub SDLC, and infrastructure as code with Terraform
• Contribute to reusable platform components for AI/ML operations
• Maintain technical documentation for internal teams and customers