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Temporary Aws Ai Practitioner Jobs (NOW HIRING)

AWS certifications such as AWS Certified, AWS Certified Machine Learning Engineer, or AWS AI Practitioner. * Experience with MLOps, CI/CD, and infrastructure-as-code tools like Terraform and ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

AWS Certified Cloud Practitioner, AWS Certified Solutions Architect (Associate), AWS Certified AI Practitioner (AIF-C01), AWS Certified Generative AI Developer (Professional - AIP-C01), AWS Certified ...

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Temporary Aws Ai Practitioner information

See salary details

$41.5K

$130.3K

$200K

How much do temporary aws ai practitioner jobs pay per year?

As of Aug 8, 2026, the average yearly pay for temporary aws ai practitioner in the United States is $130,295.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,000.00 and $150,000.00 per year, depending on experience, location, and employer.

What types of projects does a temporary AWS AI practitioner typically work on, and how do they collaborate with other team members?

Temporary AWS AI Practitioners are often brought in to support short-term projects such as deploying machine learning models, automating workflows, or assisting with data migration to AWS cloud services. They typically collaborate closely with data scientists, cloud engineers, and business stakeholders to understand requirements and implement AI solutions using AWS tools. Daily tasks may include configuring AWS AI services, optimizing model performance, and documenting solutions for handover. Effective communication and adaptability are key, as these practitioners must quickly integrate into existing teams and deliver results within tight timelines.

What is a temporary AWS AI practitioner?

Temporary AWS AI Practitioners are professionals who are hired on a short-term or contract basis to work with Amazon Web Services (AWS) artificial intelligence (AI) tools and services. They typically assist organizations with implementing, managing, or optimizing AI and machine learning solutions using AWS technologies. This role often involves tasks such as building machine learning models, integrating AWS AI services into applications, and providing technical expertise for data-driven projects. Temporary positions can range from a few weeks to several months and are ideal for organizations needing specialized AI skills for specific projects.

What is the difference between Temporary Aws Ai Practitioner vs Cloud Data Engineer?

AspectTemporary Aws Ai PractitionerCloud Data Engineer
CredentialsAWS certifications, AI/ML knowledgeAWS certifications, data engineering skills
Work EnvironmentProject-based, AI/ML-focusedData pipelines, cloud infrastructure
Employer & IndustryTech companies, AI startupsLarge enterprises, cloud service providers
Search & Comparison IntentUnderstanding AI-specific roles in AWSData infrastructure roles in cloud

The Temporary Aws Ai Practitioner primarily focuses on deploying AI and machine learning models using AWS services, often in a project-based environment. In contrast, a Cloud Data Engineer concentrates on building and maintaining data pipelines and infrastructure within cloud platforms. While both roles require AWS certifications, the Ai Practitioner emphasizes AI/ML expertise, whereas the Data Engineer emphasizes data architecture skills. Understanding these differences helps employers and job seekers target the right skills and roles in the cloud industry.

What are the key skills and qualifications needed to thrive as a temporary AWS AI practitioner, and why are they important?

To thrive as a Temporary AWS AI Practitioner, you need a solid understanding of machine learning principles, cloud computing, and AWS services, typically supported by experience or certification like AWS Certified Machine Learning – Specialty. Proficiency in using AWS AI/ML tools such as SageMaker, Rekognition, and Lambda, as well as programming languages like Python, is essential. Strong problem-solving skills, adaptability, and effective communication set top practitioners apart. These skills ensure the successful deployment of AI solutions on AWS, enabling organizations to efficiently leverage cloud-based intelligence for business value.
More about Temporary Aws Ai Practitioner jobs
What cities are hiring for Temporary Aws Ai Practitioner jobs? Cities with the most Temporary Aws Ai Practitioner job openings:
What are the most commonly searched types of Aws Ai Practitioner jobs? The most popular types of Aws Ai Practitioner jobs are:
What states have the most Temporary Aws Ai Practitioner jobs? States with the most job openings for Temporary Aws Ai Practitioner jobs include:
Infographic showing various Temporary Aws Ai Practitioner job openings in the United States as of August 2026, with employment types broken down into 74% Full Time, 22% Part Time, and 4% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $130,295 per year, or $62.6 per hour.

AWS Certified AI Practitioner (Remote)

Koniag, Inc.

Nashville, TN • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Job description

Koniag Services Inc., a Koniag Government Services company, is seeking an innovative and technically skilled AWS Certified AI Practitioner to support the design, implementation, and optimization of artificial intelligence (AI) and machine learning (ML) solutions built on the Amazon Web Services (AWS) platform for our IT Call Center serving government clients. The ideal candidate is a forward-thinking and analytically minded professional with demonstrated experience leveraging AWS AI and ML services to develop intelligent automation, predictive analytics, and natural language processing solutions that enhance the efficiency, performance, and customer experience of IT Call Center operations. They bring strong technical acumen, a passion for emerging AI technologies, and the ability to work independently and collaboratively in a fully remote environment to deliver AI-powered solutions that drive measurable operational improvements. Ability to obtain a government security clearance may be required to support Koniag Services Inc. and our government customers. This position is Remote.
We offer competitive compensation and an extraordinary benefits package including health, dental and vision insurance, 401K with company matching, flexible spending accounts, paid holidays, three weeks paid time off, and more.
Position Description:
The AWS Certified AI Practitioner will be responsible for the design, implementation, optimization, and ongoing support of AWS AI and ML solutions supporting IT Call Center operations. This individual will work closely with program leadership, the AWS Solutions Architect, the AWS Connect Administrator, data analysts, and government stakeholders to identify opportunities to leverage AI and ML capabilities to enhance call center automation, operational intelligence, and service delivery outcomes. Principal responsibilities will include but are not limited to:
  • Identify, evaluate, and implement AWS AI and ML service solutions that enhance IT Call Center operations, including intelligent automation, natural language processing, predictive analytics, sentiment analysis, and conversational AI capabilities.
  • Design, develop, and maintain AWS AI and ML solutions leveraging core AWS AI services including Amazon Lex, Amazon Polly, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon SageMaker, Amazon Bedrock, and related AWS AI and ML platform services.
  • Collaborate with the AWS Connect Administrator to design, implement, and optimize AI-powered contact center capabilities within the AWS Connect platform, including Amazon Lex-powered IVR and chatbot solutions, Amazon Transcribe Call Analytics for real-time and post-call analysis, and Amazon Connect Wisdom for AI-driven agent assistance.
  • Partner with data analysts and program leadership to develop and implement predictive analytics and machine learning models that leverage call center operational data to forecast call volumes, predict SLA risks, identify performance trends, and support data-driven operational decision making.
  • Design and implement natural language processing (NLP) and sentiment analysis solutions using Amazon Comprehend and related AWS AI services to analyze customer interactions, identify satisfaction trends, and surface actionable insights for call center quality assurance and continuous improvement programs.
  • Develop and maintain AI-powered automation solutions that streamline call center workflows, reduce manual processing requirements, and enhance agent productivity, leveraging AWS Lambda, Amazon EventBridge, AWS Step Functions, and related AWS serverless and automation services.
  • Support the development and implementation of Amazon SageMaker-based machine learning pipelines for training, testing, deploying, and monitoring custom ML models that address specific IT Call Center operational challenges and performance improvement opportunities.
  • Collaborate with the AWS Solutions Architect to ensure all AI and ML solution designs are architected in alignment with program-wide AWS cloud architecture standards, security requirements, and FedRAMP compliance obligations.
  • Conduct regular assessments of deployed AI and ML solutions, monitoring model performance, accuracy, and operational impact, and implementing updates, retraining, and optimization activities to maintain solution effectiveness over time.
  • Develop and maintain comprehensive technical documentation for all AI and ML solutions including solution design documents, architecture diagrams, model documentation, data flow diagrams, and operational runbooks.
  • Stay current on AWS AI and ML platform updates, new service releases, emerging AI technologies, and industry best practices, proactively identifying opportunities to leverage new AWS AI capabilities to enhance IT Call Center performance and customer experience.
  • Provide technical guidance and subject matter expertise to program leadership, operations staff, and data analysts on AWS AI and ML service capabilities, solution design approaches, and responsible AI principles and practices.
  • Ensure all AWS AI and ML solution design and implementation activities comply with applicable federal security requirements, AWS GovCloud policies, FedRAMP authorization requirements, data privacy regulations, and responsible AI governance standards.
  • Support the development and delivery of training materials and knowledge sharing sessions for program staff on deployed AI and ML solutions, ensuring all relevant team members understand solution capabilities, limitations, and appropriate use cases.
  • Contribute to business development activities as needed, including supporting proposal efforts with AI and ML capability narratives, technical solution concepts, and relevant past performance documentation.

Education and Experience:
Required:
  • Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Information Technology, Mathematics, or a related field from an accredited college or university. Relevant experience may be considered in lieu of a degree.
  • 3+ years of hands-on experience designing, implementing, and managing AWS AI and ML solutions in a structured IT service delivery or data-driven operational environment.
  • Demonstrated experience developing and deploying solutions leveraging AWS AI services including Amazon Lex, Amazon Comprehend, Amazon Transcribe, Amazon Polly, and/or Amazon SageMaker.
  • Experience integrating AWS AI and ML services with cloud-based operational platforms and enterprise systems.
  • AWS Certified AI Practitioner certification (required at time of hire).

Preferred:
  • Prior experience designing and implementing AWS AI and ML solutions within a federal government contracting or AWS GovCloud environment.
  • Experience supporting AI and ML solution development for an IT call center, service desk, or IT managed services program, including experience with AWS Connect AI-powered contact center capabilities.
  • AWS Certified Machine Learning - Specialty certification or demonstrated progress toward obtaining the certification.
  • Experience working in a fully remote AI and ML development role within a government contracting environment.

Required Skills and Competencies:
  • Strong communication skills in English - both written and oral - with the ability to present complex AI and ML solution designs, technical findings, and strategic recommendations clearly and effectively to both technical and non-technical audiences including program leadership and government stakeholders in a remote work environment.
  • Demonstrated hands-on proficiency in designing and implementing AWS AI and ML solutions leveraging a broad portfolio of AWS AI services including Amazon Lex, Amazon Polly, Amazon Comprehend, Amazon Transcribe, Amazon Rekognition, Amazon SageMaker, and Amazon Bedrock.
  • Strong working knowledge of natural language processing (NLP), conversational AI, sentiment analysis, speech-to-text, and text-to-speech concepts and their practical application within AWS AI service implementations.
  • Proficiency in Amazon SageMaker for the development, training, deployment, and monitoring of custom machine learning models, including experience with SageMaker Studio, SageMaker Pipelines, and SageMaker Model Monitor.
  • Working knowledge of AWS Connect AI-powered contact center capabilities including Amazon Lex IVR and chatbot integration, Amazon Transcribe Call Analytics, Amazon Connect Wisdom, and Amazon Connect Customer Profiles.
  • Proficiency in serverless and automation services such as AWS Lambda, Amazon EventBridge, and AWS Step Functions for the development of AI-powered workflow automation solutions.
  • Strong understanding of machine learning concepts including supervised and unsupervised learning, model training and evaluation, feature engineering, and model deployment and monitoring best practices.
  • Proficiency in scripting or programming languages such as Python for ML model development, AWS Lambda function development, data processing, and AI solution automation.
  • Working knowledge of AWS security and compliance principles as they apply to AI and ML solution design, including data privacy, IAM policy configuration, and FedRAMP compliance considerations.
  • Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint, Outlook) and remote collaboration tools such as Microsoft Teams and SharePoint for documentation, communication, and coordination purposes.
  • Ability to obtain and maintain a government security clearance as required.

Desired Skills and Competencies:
  • Active government security clearance (Secret or higher).
  • AWS Certified Machine Learning - Specialty certification.
  • AWS Certified Solutions Architect - Associate or Professional certification.
  • AWS Certified AI Practitioner certification.
  • Experience designing and implementing AWS AI and ML solutions within an AWS GovCloud environment in support of federal government FedRAMP authorization and data privacy requirements.
  • Familiarity with federal IT security frameworks and compliance requirements such as NIST SP 800-53, FedRAMP, FISMA, and emerging federal AI governance frameworks as they relate to AI and ML solution design and deployment.
  • Experience with Amazon Bedrock and large language model (LLM) integration for generative AI application development within a government IT service delivery context.
  • Familiarity with responsible AI principles, AI ethics frameworks, and bias detection and mitigation strategies as they apply to AI and ML solution development and deployment in a federal government environment.
  • Experience with data engineering and ML pipeline development tools including AWS Glue, Amazon Kinesis, Amazon Redshift, and related AWS data processing and storage services.
  • Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn for custom model development and integration with AWS SageMaker.
  • Experience with MLOps principles and practices including model versioning, continuous integration and delivery for ML pipelines, and automated model retraining and monitoring.
  • Familiarity with Amazon QuickSight or equivalent cloud-based business intelligence platforms for AI and ML solution performance reporting and operational analytics.
  • ITIL Foundation certification or higher demonstrating knowledge of IT service management principles relevant to AI-powered IT call center operations.
  • Experience contributing to business development efforts including proposal writing, AI and ML capability development narratives, and past performance documentation.
  • Knowledge of conversational AI design principles and best practices for developing effective and accessible IVR and chatbot experiences within a government IT call center context.

Our Equal Employment Opportunity Policy:
The company is an equal opportunity employer. The company shall not discriminate against any employee or applicant because of race, color, religion, creed, ethnicity, sex, sexual orientation, gender or gender identity (except where gender is a bona fide occupational qualification), national origin or ancestry, age, disability, citizenship, military/veteran status, marital status, genetic information or any other characteristic protected by applicable federal, state, or local law. We are committed to equal employment opportunity in all decisions related to employment, promotion, wages, benefits, and all other privileges, terms, and conditions of employment.
The company is dedicated to seeking all qualified applicants. If you require an accommodation to navigate or to apply to a position on our website, please contact Heaven Wood via e-mail at accommodations@koniag-gs.com or by calling 703-488-9377 to request accommodations.
Koniag Government Services (KGS) is an Alaska Native Owned corporation supporting the values and traditions of our native communities through an agile employee and corporate culture that delivers Enterprise Solutions, Professional Services and Operational Management to Federal Government Agencies. As a wholly owned subsidiary of Koniag, we apply our proven commercial solutions to a deep knowledge of Defense and Civilian missions to provide forward leaning technical, professional, and operational solutions. KGS enables successful mission outcomes for our customers through solution-oriented business partnerships and a commitment to exceptional service delivery. We ensure long-term success with a continuous improvement approach while balancing the collective interests of our customers, employees, and native communities. For more information, please visit www.koniag-gs.com.
Equal Opportunity Employer/Veterans/Disabled. Shareholder Preference in accordance with Public Law 88-352

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About Koniag

Sourced by ZipRecruiter

Industry

Investment management and consulting services

Company size

501 - 1,000 Employees

Headquarters location

Kodiak, AK, US

Year founded

1972

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