SageMaker

SageMaker Engineer Jobs

20 jobs found

Today

AWS AI Engineer

Hudson Manpower Morton Grove, IL 🇺🇸 Remote

Morton Grove, IL

Today

Full time Backend Developer AI Amazon Web Services

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Job Description

Senior AWS AI Engineer responsible for delivering AI/ML applications on AWS, focusing on retrieval-augmented generation (RAG), fine-tuning LLMs, and AWS-native microservices for enterprise automation.

Responsibilities

Hands-on work with AWS services such as AWS Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate AI/ML capabilities.
Design and implement AWS cloud services spanning infrastructure, ML platforms, and AI services to support enterprise automation.
Develop LLM based applications, including Retrieval-Augmented Generation using LangChain and other frameworks.
Build cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborate with stakeholders to translate business goals into secure, scalable AI systems.
Own the software release lifecycle, managing CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Support development and evolution of reusable platform components for AI/ML operations.
Create and maintain technical documentation for the team and internal customers.
Demonstrate excellent verbal and written communication skills in English.

Requirements

Hands-on experience with AWS services such as Bedrock, SageMaker, ECS, and Lambda.
Experience with AWS Organizations and policy guardrails, including SCPs and AWS Config.
Proven experience implementing RAG architectures and working with ML frameworks/tools such as Transformers, PyTorch, TensorFlow, and LangChain.
Strong Infrastructure as Code practices and experience building Terraform modules for AWS.
Fine-tuning large language models, building datasets, and deploying ML models to production.
Experience with Git-based version control, code reviews, and DevOps workflows.
Minimum 7 years of relevant professional experience.

Technologies

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

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

Top Skills

Must Have
- AWS Bedrock
- AWS SageMaker
- AWS ECS
- AWS Lambda
- 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 LLMs, 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
- Data privacy and compliance best practices (PII handling, secure model deployment)
- Data science background or experience with structured/unstructured data
- Exposure to FinOps and cloud cost optimization
- Hugging Face, Node.js
- Policy as Code development (Terraform Sentinel)

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Today

AWS AI Engineer

Hudson Manpower Redmond, WA 🇺🇸 Remote

Redmond, WA

Today

Full time Backend Developer AI Amazon Web Services

Apply Now

Job Description

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)

View full job page →

Today

AWS AI Engineer

Hudson Manpower Sunnyvale, CA 🇺🇸 Remote

Sunnyvale, CA

Today

Full time AI Artificial Intelligence Automation

Apply Now

Job Description

The role is for a senior AWS AI Engineer at Hudson Manpower, based in Sunnyvale, California with remote working options. The position centers on developing cloud-native AI/ML applications, with a focus on retrieval-augmented generation, fine-tuning large language models, and deploying AWS-based microservices for an enterprise production environment.

Responsibilities

Hands-on development with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and operate AI/ML workloads.
Lead the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
Work with LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and related frameworks.
Develop cloud-native microservices, APIs, and serverless functions to support 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.
Demonstrate strong verbal and written communication skills in English.

Requirements

Minimum of 7 years of hands-on software engineering experience with a strong emphasis on Python.
Experience with AWS services, particularly Bedrock or SageMaker.
Familiarity with fine-tuning large language models and deploying ML models to production, including dataset creation.
Proven experience with AWS Organizations and policy guardrails such as SCP and AWS Config.
Solid background in implementing Retrieval-Augmented Generation (RAG) architectures and LangChain.
Proficiency in Infrastructure as Code practices and building Terraform modules for AWS cloud environments.
Strong background in Git-based version control, code reviews, and DevOps workflows.
History of delivering production-ready software with integrated release pipelines.

Technologies

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

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 offering
Eligibility for referral bonuses

Supervisory Responsibilities

None

View full job page →

1d ago

AWS AI Engineer

Hudson Manpower New Jersey 🇺🇸 Remote

New Jersey

1d ago

Full time Amazon Web Services Artificial Intelligence AWS

Apply Now

Job Description

Hudson Manpower is seeking a Senior AWS AI Engineer to design and operate retrieval-augmented generation systems, fine-tune large language models, and deliver cloud-native AI services within an enterprise AWS environment. This remote-friendly role is based in New Jersey and offers a collaborative culture, clear ownership of AI workflows, and the chance to influence how AI solutions support business outcomes.

You will join a team that values open communication, structured CI/CD processes, and a focus on building secure, scalable AI capabilities. The position comes with a competitive compensation package, comprehensive health coverage, and ongoing professional development opportunities.

Responsibilities

Hands-on work with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3
Own the implementation of AWS cloud services across infrastructure, machine learning, and AI platform services
Develop LLM-based applications, including Retrieval-Augmented Generation (RAG) using LangChain and other 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 in English

Requirements

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

Technologies

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

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

Supervisory Responsibilities

None

View full job page →

2d ago

AWS AI Engineer

Hudson Manpower Richmond, VA 🇺🇸 Remote

Richmond, VA

2d ago

Full time Backend Developer AI Ai Workflows

Apply Now

Job Description

Hudson Manpower is seeking an accomplished AWS AI Engineer to lead hands-on development of retrieval-augmented generation solutions and refine large language models. This senior role, based in Richmond, Virginia with remote work flexibility, focuses on deploying AWS-native microservices to advance automation and governance in production environments. The ideal candidate brings a strong Python background and a proven ability to translate complex requirements into scalable AI systems on AWS.

Responsibilities

Engage hands-on with AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to build and deploy AI-enabled solutions.
Design and implement AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
Develop and deploy LLM-based applications, including Retrieval-Augmented Generation (RAG) workflows using LangChain and related frameworks.
Create cloud-native microservices, APIs, and serverless functions to enable intelligent automation and real-time data processing.
Collaborate with internal stakeholders to map business goals into secure, scalable AI architectures.
Own the software release lifecycle, including CI/CD pipelines, GitHub-based SDLC, and infrastructure as code with Terraform.
Contribute to 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 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 background with AWS organizations and policy guardrails (SCP, AWS Config).
Proven experience implementing RAG architectures and using LangChain.
Strong IaC practices and experience building Terraform modules for AWS cloud environments.
Robust background in Git-based version control, code reviews, and DevOps workflows.
History of delivering production-ready software with integrated release pipelines.

Technologies

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

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
Eligibility for referral bonuses

What you’ll get

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
Eligibility for referral bonuses

View full job page →

2d ago

AWS AI Engineer

Hudson Manpower San Jose, CA 🇺🇸 Remote

San Jose, CA

2d ago

Full time AI Ai Workflows Artificial Intelligence

Apply Now

Job Description

Hudson Manpower is seeking a senior AWS AI Engineer to join their San Jose area team with remote work options. The role centers on hands-on development of AI and ML applications in AWS, with a focus on retrieval-augmented generation (RAG), fine-tuning large language models, and building AWS-native microservices to support enterprise automation and governance.

Responsibilities

Hands-on development across AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
Own the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform services.
Work with LLM-based applications, including RAG approaches using LangChain and similar 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.
Demonstrate strong English communication skills, both verbal and written.

Requirements

Seven years of hands-on software engineering experience with a strong emphasis on Python.
Experience with AWS services, notably Bedrock or SageMaker.
Familiarity with fine-tuning large language models or building datasets and deploying ML models to production.
Experience with AWS Organizations and policy guardrails such as SCPs and AWS Config.
Proven ability to implement RAG architectures and work with LangChain.
Experience in infrastructure as code best practices and building Terraform modules for AWS.
Solid background in Git-based version control, code reviews, and DevOps workflows.
Proven success delivering production-ready software with integrated release pipelines.

Technologies

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

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
Eligible for referral bonuses

Supervisory Responsibilities

None

Nice-to-Haves

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

View full job page →

3d ago

AWS AI Engineer

Hudson Manpower Buffalo Grove, IL 🇺🇸 Remote

Buffalo Grove, IL

3d ago

Full time AI Amazon Web Services Artificial Intelligence

Apply Now

Job Description

The AWS AI Engineer role is a senior position focused on designing and delivering production-grade AI and ML capabilities on AWS. The emphasis is on retrieval-augmented generation, fine-tuning large language models, and building AWS-native microservices to support enterprise automation and governance.

Responsibilities

Hands-on development with AWS services including Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3.
Architect and implement AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities.
Build and deploy LLM-based applications, including Retrieval-Augmented Generation using LangChain and other frameworks.
Develop cloud-native microservices, APIs, and serverless components 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.
Contribute to reusable platform components for AI/ML operations and tooling.
Create and maintain technical documentation for teams and internal customers.
Maintain strong written and verbal communication in English.

Requirements

Minimum of seven years of hands-on software engineering experience with a strong emphasis on Python.
Proficiency with AWS services, particularly Bedrock, SageMaker, ECS, and Lambda.
Experience with AWS Organizations and policy guardrails, including SCP and AWS Config.
Background in Retrieval-Augmented Generation architectures and using LangChain and other frameworks.
Experience fine-tuning large language models, building datasets, and deploying ML models to production.
Demonstrated IaC expertise, including building Terraform modules for AWS.
Solid Git-based version control practices, code reviews, and DevOps workflows.
Track record of delivering production-ready software with integrated release pipelines.

Technologies

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

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

Supervisory Responsibilities

None

Minimum Knowledge, Skills, and Abilities Required

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

Nice-to-Haves

AWS or relevant cloud certifications.
Policy as Code development, e.g., 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, including PII handling and secure model deployment.