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Remote Aws Jobs in Tennessee (NOW HIRING)

AWS Connect Admin

Nashville, TN · Remote

$17.50 - $24/hr

... AWS Connect and related AWS services, a strong understanding of cloud-based contact center ... This position is Remote. We offer competitive compensation and an extraordinary benefits package ...

New

Partner with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS, leveraging Amazon SageMaker, Amazon Bedrock ...

New

Senior Cloud DevOps Engineer

Franklin, TN · Remote

$125K - $161K/yr

Remote - USA The Senior DevOps Cloud Engineer will design, implement, and maintain scalable, secure ... Build and optimize CI/CD pipelines in Azure DevOps and AWS CodePipeline/CodeBuild, enabling ...

Experience designing and deploying solutions to cloud environments (AWS) * Experience with IaC ... Candidate can live anywhere in the United States. #LI-MP2 #LI-REMOTE Basic Requirements * 8+ years ...

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Showing results 1-20

Remote Aws information

See Tennessee salary details

$10

$49

$70

How much do remote aws jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for remote aws in Tennessee is $49.06, according to ZipRecruiter salary data. Most workers in this role earn between $35.14 and $58.46 per hour, depending on experience, location, and employer.

What are the qualifications to get a remote AWS job?

The qualifications you need differ based on your career choice. In many cases, a technology-related bachelor’s degree is necessary. You should pursue coursework and training that grants skills and experience with specific scripting language types, such as Ruby, Shell, Python, and Perl. Knowledge of monitoring tools, coding, and similar technology skills can also be helpful. For some positions, having a related certification may help you to stand out above the other applicants for a specific job.

What are some common challenges faced by remote AWS engineers, and how can they be addressed?

Remote AWS engineers often encounter challenges such as maintaining clear communication with geographically dispersed teams and managing cloud infrastructure securely from afar. To address these issues, it's important to use collaboration tools like Slack or Microsoft Teams, adhere to robust version control and documentation practices, and follow AWS security best practices such as using IAM roles and multi-factor authentication. Regular virtual meetings and clear project management protocols also help ensure everyone stays aligned and productive.

What is the difference between Remote Aws vs Remote Cloud Engineer?

AspectRemote AwsRemote Cloud Engineer
CertificationsAWS Certified Solutions Architect, AWS Certified DeveloperAWS certifications, Azure, Google Cloud certifications
Work EnvironmentPrimarily cloud-based, AWS platform focusMulti-cloud or cloud-agnostic, various cloud platforms
Industry UsageTech, finance, healthcare, retailTech, finance, healthcare, retail
Job FocusDesigning, deploying, managing AWS infrastructureDesigning, deploying, managing cloud solutions across platforms

Remote Aws roles focus specifically on AWS cloud services, infrastructure, and certifications. Remote Cloud Engineer positions often require knowledge of multiple cloud platforms and broader cloud architecture skills. While both roles work remotely and in similar industries, Remote Aws specialists concentrate on AWS-specific tasks, whereas Remote Cloud Engineers handle multi-cloud environments.

Are remote AWS jobs still in demand?

Remote AWS jobs remain in high demand due to the widespread adoption of cloud computing and the need for cloud infrastructure management. Skills in AWS services, certifications like AWS Certified Solutions Architect, and experience with automation tools increase employability in this field.
What are the most commonly searched types of Aws jobs in Tennessee? The most popular types of Aws jobs in Tennessee are:
What cities in Tennessee are hiring for Remote Aws jobs? Cities in Tennessee with the most Remote Aws job openings:
Infographic showing various Remote Aws job openings in Tennessee as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% Remote job distribution, with an average salary of $102,036 per year, or $49.1 per hour.

AWS Certified AI Practitioner (Remote)

kgs

Nashville, TN • Remote

Other

Medical, Dental, Vision, Retirement, PTO

Posted 2 days ago

New


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