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Contract Amazon Bedrock Jobs (NOW HIRING)

Vings Technologies

Snowflake Solutions Architect

Keyport, NJ · On-site

$65 - $85.75/hr

Union Beach, NJ - Hybrid 3 days in a week Tues, Wed & Thurs Contract: 6-9+ months. Experience: 10+ ... Amazon Bedrock (Agents/Knowledge Bases/Guardrails) . The role will partner with business and ...

Staffingine LLC

AI Engineer

Malvern, PA · On-site

$42 - $52/hr

Malvern, PA Job Type: Contract * Design, build, and optimize AI agents tailored to specific ... Work with Amazon Bedrock to integrate and orchestrate generative AI services * Collaborate with ...

Kanak Elite Services Inc

AI Engineer

Malvern, PA · On-site

Malvern PA Hybrid Duration : Long term contract Responsibilities * Design, develop, and deploy GenAI solutions on platforms like Amazon bedrock and Amazon Q Business. * Build and orchestrate AI ...

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All JobsContract Amazon Bedrock Jobs

Contract Amazon Bedrock information

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How much do contract amazon bedrock jobs pay per year?

As of Jul 20, 2026, the average yearly pay for contract amazon bedrock in the United States is $110,301.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What are Contract Amazon Bedrock roles?

Contract Amazon Bedrock roles typically refer to temporary or project-based positions that focus on implementing, managing, or supporting Amazon Bedrock, a fully managed service for building and scaling generative AI applications. Contractors in these roles may work on tasks such as integrating Bedrock’s foundation models into business solutions, optimizing AI workflows, or providing technical support to clients. These positions are usually offered through staffing agencies or as independent contracts, providing flexibility for both employers and professionals with expertise in AI, cloud computing, and Amazon Web Services (AWS).

What are the key skills and qualifications needed to thrive as a Contract Amazon Bedrock Specialist, and why are they important?

To thrive as a Contract Amazon Bedrock Specialist, you need expertise in cloud computing, machine learning, and foundational knowledge of generative AI, often supported by a degree in computer science or a related field. Familiarity with AWS Bedrock, Amazon Web Services, API integration, and relevant certifications such as AWS Certified Machine Learning are highly valuable. Strong problem-solving, adaptability, and effective communication skills help in translating client needs into scalable AI solutions. These skills ensure the successful design, deployment, and management of AI-powered applications on AWS, meeting both technical and business objectives.

Is Amazon Bedrock worth it?

Amazon Bedrock is a managed service that provides access to foundation models for building AI applications, making it valuable for roles involving AI development and machine learning. Its worth depends on the specific project needs, skill level with cloud services, and the cost-benefit analysis of integrating AI models into workflows.

Will Amazon really pay you to work from home?

Contract Amazon Bedrock roles often offer remote work options, allowing employees to work from home depending on the position and company policies. These jobs typically require skills in cloud services and may involve flexible schedules, but pay and remote arrangements vary by role and location.

Is Amazon Bedrock paid?

Contract Amazon Bedrock roles are typically paid positions, with compensation determined by the specific contract terms, experience, and job responsibilities. These roles often require skills in cloud services and AI technologies and may involve flexible schedules depending on the project.

How does a Contract Amazon Bedrock specialist typically collaborate with cross-functional teams during client projects?

A Contract Amazon Bedrock specialist frequently works alongside data scientists, machine learning engineers, and project managers to implement AI and machine learning solutions using Amazon Bedrock services. Collaboration often involves understanding client requirements, designing tailored solutions, integrating Bedrock APIs, and troubleshooting deployment issues. Regular communication and agile development practices help ensure that deliverables meet both technical standards and client expectations, making teamwork and adaptability crucial for success.

How does the Amazon Bedrock agent work?

In the context of a Contract Amazon Bedrock role, the agent typically refers to a software component or system that interacts with Amazon Bedrock services to facilitate tasks such as deploying, managing, or monitoring machine learning models. The agent communicates with Bedrock APIs, automates workflows, and may require knowledge of cloud environments and scripting skills. It operates within a secure environment to ensure data integrity and compliance with AWS standards.
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Contract Amazon Bedrock jobs near you
Infographic showing various Contract Amazon Bedrock job openings in the United States as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $110,301 per year, or $53 per hour.

AWS AI Architect (AWS Bedrock Expertise)

Vish Consulting IT

Seattle, WA • On-site

$73.75 - $96.75/hr

Contractor

Re-posted 20 days ago

Job description

Job Role: AWS AI Architect (AWS Bedrock Expertise)

Location: Seattle, WA or Miami, FL (Hybrid)

Contract Role

Position Overview

We are seeking an experienced AWS AI Architect with deep hands‑on expertise in Amazon Bedrock to design, architect, and implement end‑to‑end Generative AI and LLM‑powered solutions. The ideal candidate will combine strong cloud architecture skills with applied AI knowledge to build scalable, secure, enterprise-grade AI platforms and applications on AWS.

Key Responsibilities:

AI & Solution Architecture:

  • Design and architect Generative AI solutions using Amazon Bedrock, including model selection, orchestration, security, and deployment.
  • Build Retrieval-Augmented Generation (RAG) pipelines using Amazon OpenSearch, Aurora ML Vector Engine, DynamoDB, or 3rd‑party vector databases.
  • Evaluate foundation models (Claude, Llama, Amazon Titan, Cohere Command) and recommend the right model per use case.
  • Architect multi-agent GenAI systems using Bedrock Agents and Bedrock Knowledge Bases.
  • Develop end‑to‑end AI workflows using Lambda, Step Functions, API Gateway, and other serverless components.

Model Development & Engineering:

  • Implement prompt engineering, prompt optimization, and evaluation frameworks.
  • Customize and fine‑tune LLMs through Bedrock Fine‑Tuning workflows.
  • Create reusable GenAI components, patterns, and accelerators for enterprise adoption.
  • Integrate Bedrock with enterprise data lakes, APIs, and backend systems.

Data & Integration:

  • Build scalable ingestion and preprocessing pipelines using Glue, S3, EMR, Redshift, Kinesis, etc.
  • Architect secure access patterns using IAM, VPC, PrivateLink, KMS, and guardrails for responsible AI.
  • Implement observability, governance, and monitoring using CloudWatch, CloudTrail, and SageMaker MLOps.

Leadership & Collaboration:

  • Lead architecture reviews, technical deep dives, and PoCs across business units.
  • Work closely with product, engineering, and business teams to translate needs into scalable AI solutions.
  • Mentor teams on GenAI, Bedrock best practices, and AWS architecture standards.

Required Skills & Qualifications:

  • 7+ years of experience in cloud architecture (AWS preferred).
  • 3+ years of hands-on experience in AI/ML, with at least 1–2 years in Generative AI solutions.
  • Strong expertise with Amazon Bedrock (mandatory).
  • Experience with major foundation models (Claude, Llama, Titan, Cohere).
  • Strong command of Python, API-based integrations, and serverless application development.
  • Proven experience implementing RAG architectures at scale.
  • Deep understanding of cloud security, networking, and identity (IAM, KMS, VPC).
  • Hands-on with vector databases and embedding strategies.
  • AWS certifications preferred:
    • AWS Certified Solutions Architect – Professional
    • AWS Certified Machine Learning – Specialty

Preferred Qualifications:

  • Experience with SageMaker, EKS, or ECS for model deployment and experimentation.
  • Understanding of responsible AI, content filters, and enterprise guardrails.
  • Background in building enterprise copilots, chatbots, and document intelligence solutions.
  • Familiarity with event-driven architectures using EventBridge.

Thanks & Regards,

Vivek Sharma 

Account Manager

Email: vivek@vishusa.com

Vish Consulting Services, Inc

www.vishusa.com