Aws Bedrock

Aws Bedrock Engineer Jobs

15 jobs found

1d ago

Lead Applied AI Engineer II

Deloitte Washington, DC

Washington, DC

1d ago

$119k - $244k/yr Full time Artificial Intelligence AWS Aws Bedrock

Apply Now

Job Description

Deloitte is seeking a Lead Applied AI Engineer II for an onsite role in Washington, DC. The position centers on hands-on software engineering across high-visibility initiatives, with an emphasis on delivering customer outcomes and tangible business value. The role also invites you to model technical leadership and mentor cross-functional teams to design, build, and deploy advanced solutions. Salary ranges from USD 118,700 to 243,700 per year. A bachelor’s degree and at least six years of relevant experience are required.

Responsibilities

Outcome driven accountability: uphold a culture focused on customer and business outcomes, delivering engineering solutions that solve complex problems with measurable value while maintaining lean, high‑quality designs and implementations.
Technical leadership and advocacy: act as the product’s technical champion, validating code quality and feasibility and aligning work with business and customer goals. lead requirements analysis, low‑level architecture and component design, development, testing, integrations, and support.
Engineering craftsmanship: safeguard architecture integrity and the enterprise standards across the tech stack. manage dependencies, design, implementation, quality, data, and ongoing maintenance. remain hands-on, continuously learn new approaches, and create technical specifications; produce high‑quality, scalable code and review peers’ code while mentoring them to ensure quality.
Customer centric engineering: develop lean solutions through rapid, low‑cost experimentation to address customer needs. engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
Incremental and iterative delivery: adopt a forward‑leaning mindset that emphasizes action and evidence over heavy planning, delivering lean, maintainable solutions that navigate complexity.
Cross-functional collaboration and integration: work with empowered product management, experience, and delivery teams; integrate diverse perspectives to balance feasibility, viability, usability, and value, fostering a collaborative environment that drives innovation.
Advanced technical proficiency: demonstrate deep expertise in modern software engineering practices, including AI and Agentic SSDLC, delivering daily product deployments with full automation from discovery to production to operations and quality checks throughout the SSDLC lifecycle. be a role model and apply these techniques to optimize solutioning and delivery, while focusing on the full lifecycle of product development and continuous improvement.
Domain expertise: rapidly acquire domain knowledge relevant to the business or product; translate business needs, architectures, and UX/UI designs into technical specifications and code; contribute as a flexible, quality‑driven teammate mindful of tech debt payoff.
Effective communication and influence: communicate complex technical concepts clearly and persuasively, inspiring teammates and product teams through well‑structured arguments and evidence‑based trade‑offs; craft narratives that align technical solutions with business objectives.
Engagement and collaborative co‑creation: collaborate with product engineering teams at all levels, including customers when needed; build constructive relationships and foster a culture of co‑creation and shared momentum toward product goals; align diverse perspectives to reach feasible solutions.

Requirements

Bachelor’s degree in computer science, software engineering, data science, machine learning, or a related discipline.
Six or more years of experience with technologies such as Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, and relevant unit testing frameworks.
Three or more years building AI/ML applications, with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open‑source models), RAG pipelines, prompt engineering, and vector databases.
Three or more years of cloud‑native engineering using FaaS, PaaS, or microservices on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
One or more years establishing engineering standards, including actively leading, mentoring, and guiding team members in adopting and improving these standards.
Prior software engineering experience with Business Context Diagrams, sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, code instrumentation, and AI augmented, spec‑driven development.
Experience using XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow, and agentic AI frameworks (for example LangFuse, LangSmith, or similar multi‑agent orchestration tools) to deliver high quality products rapidly.

Technologies

Angular, React, NodeJS, Python, C#, .NET, Java
SQL/NoSQL, PyTorch, TensorFlow
LangChain, LangGraph
OpenAI, Anthropic, LangFuse, LangSmith
Azure, AWS, GCP; Azure OpenAI, AWS Bedrock, Vertex AI
FaaS, PaaS, MLflow
ADO, GitHub, SonarQube

The Successful Candidate Will Possess

Excellent interpersonal and organizational skills, with the ability to handle diverse situations, manage complex projects, and adapt to changing priorities with professionalism and empathy.

Other

Travel availability of approximately 10 percent, depending on project requirements.
Limited immigration sponsorship may be available.
The stated wage range reflects a broad range of factors considered in compensation decisions, including skill, experience, and business needs; geographic differentials may apply.
You may be eligible for a discretionary annual incentive program, subject to program rules and individual and organizational performance.

View full job page →

1d ago

AWS AI Engineer

Hudson Manpower Richmond, VA 🇺🇸 Remote

Richmond, VA

1d 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 →

1d ago

AWS AI Engineer

Hudson Manpower San Jose, CA 🇺🇸 Remote

San Jose, CA

1d 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 →

2d ago

AWS AI Engineer

Hudson Manpower Buffalo Grove, IL 🇺🇸 Remote

Buffalo Grove, IL

2d 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.

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
Referral bonuses

View full job page →

3d ago

AWS AI Engineer

Hudson Manpower Scottsdale, AZ 🇺🇸 Remote

Scottsdale, AZ

3d ago

Full time AI Amazon Web Services Artificial Intelligence

Apply Now

Job Description

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

View full job page →

4d ago

AWS AI Engineer

Hudson Manpower Wilmington, NC 🇺🇸 Remote

Wilmington, NC

4d ago

Full time AI Artificial Intelligence Automation

Apply Now

Job Description

Hudson Manpower is seeking a Senior AI AWS Engineer in Wilmington, NC with remote-friendly options. This role focuses on building production-grade AI and ML services on AWS, including retrieval-augmented generation, fine-tuning large language models, and cloud-native microservices within an enterprise setting. You’ll work hands-on to design scalable, secure AI systems that connect to live data and infrastructure, supported by a competitive compensation package and robust benefits.

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

Responsibilities

Apply AWS services such as Lambda, Bedrock, SageMaker, Step Functions, DynamoDB, and S3 to implement cloud-native AI solutions
Own the implementation of AWS cloud services spanning infrastructure, machine learning, and AI platform capabilities
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 with CI/CD pipelines, GitHub-based SDLC, and infrastructure as code via 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
Communicate effectively in English, both verbally and in writing

Requirements

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 or building datasets and deploying ML models to production
Experience with AWS Organizations and policy guardrails (SCP, AWS Config)
Solid background in implementing Retrieval-Augmented Generation architectures and using LangChain
Experience with Infrastructure as Code best practices and building Terraform modules for AWS
Strong Git-based version control, code reviews, and DevOps workflows
Track record of delivering production-ready software with integrated release pipelines
AWS or relevant cloud certifications
Data privacy and compliance best practices (PII handling, secure model deployment)
Data science background or experience working with structured and unstructured data
Exposure to FinOps and cloud cost optimization
Experience with Hugging Face and Node.js
Policy as Code development experience (Terraform Sentinel)

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

View full job page →

6d ago

Lead Applied AI Engineer II

Deloitte Honolulu, HI

Honolulu, HI

6d ago

$119k - $244k/yr Full time Artificial Intelligence AWS Aws Bedrock

Apply Now

Job Description

Hands-on Lead Applied AI Engineer delivering AI-enabled software solutions on high-visibility Deloitte projects from onsite in Honolulu, HI, with technical leadership and cross-functional collaboration.

Responsibilities

Accountability for customer and business outcomes; design lean, high-quality engineering solutions that solve complex problems and deliver tangible value.
Technical leadership and advocacy for products; ensure code integrity and alignment with business goals; lead requirements analysis, low-level architecture and component design, development, testing, integrations, and support.
Engineering craftsmanship; maintain architecture and stack integrity to enterprise standards; manage dependencies, code design, implementation quality, data handling, and ongoing maintenance and operations; stay hands-on and continuously learn new approaches, languages, and frameworks; create technical specifications and produce high-quality, maintainable code; review peers and mentor them to uphold quality.
Customer-centric engineering; develop lean solutions through rapid, inexpensive experiments and engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time.
Incremental and iterative delivery; embrace action and evidence over extensive planning; navigate complexity with a forward-leaning approach to deliver lean, supported, and maintainable solutions.
Cross-functional collaboration and integration; work with product management, experience, and delivery teams; integrate diverse perspectives to balance feasibility, viability, usability, and value; foster a collaborative environment that spurs innovation.
Advanced technical proficiency; demonstrate deep expertise in modern software engineering practices, including AI and agentic SDLC, enabling daily product deployments with full automation from discovery to production to operations and quality checks throughout the lifecycle.
Domain expertise; rapidly acquire domain knowledge relevant to the business or product; translate business needs, architectures, and UX/UI designs into technical specifications and code; be a reliable, quality-focused teammate who supports others and pays down tech debt.
Effective communication and influence; articulate complex technical concepts clearly and persuasively; build evidence-backed trade-offs and narratives that align technical solutions with business objectives.
Engagement and collaborative co-creation; collaborate with product engineering teams at all levels and with customers as needed; cultivate constructive relationships and drive consensus toward feasible solutions.

Requirements

Excellent interpersonal and organizational skills; able to manage diverse situations, complex projects, and shifting priorities with empathy and care.
Bachelor's degree in computer science, software engineering, data science, machine learning, or a related discipline; experience is a key factor.
6+ years of experience across most of the following: Angular, React, NodeJS, Python, C#, .NET, Java, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, plus unit testing frameworks.
3+ years building AI/ML applications with hands-on GenAI experience across LLM integration (OpenAI, Anthropic, or open-source models), RAG pipelines, prompt engineering, and vector databases.
3+ years cloud-native engineering using FaaS, PaaS, or microservices on Azure, AWS, or GCP, including AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI.
1+ years establishing engineering standards, including actively leading and mentoring team members in adoption and continuous improvement.
Prior software engineering experience with Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, code instrumentation, and AI augmented spec-driven development.
Experience with XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, MLflow and agentic AI frameworks (eg, LangFuse, LangSmith, or equivalent multi-agent orchestration tools) to deliver high-quality products rapidly.