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Overnight Aws Ai Practitioner Jobs (NOW HIRING)

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 ...

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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Overnight Aws Ai Practitioner information

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$24K

$112.3K

$158K

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

As of Sep 2, 2026, the average yearly pay for overnight aws ai practitioner in the United States is $112,339.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $131,000.00 per year, depending on experience, location, and employer.

What does an Overnight AWS AI Practitioner do?

An Overnight AWS AI Practitioner is responsible for managing and supporting artificial intelligence and machine learning workloads on Amazon Web Services (AWS) during nighttime or after-hours shifts. Their duties typically include monitoring AI systems, troubleshooting issues, deploying models, and ensuring that automated processes run smoothly overnight. This role is essential for organizations that require 24/7 AI operations, such as global businesses or companies with critical real-time applications. Practitioners often collaborate remotely with data scientists, engineers, and support teams to maintain system uptime and data integrity through the night.

What are the key skills and qualifications needed to thrive as an Overnight AWS AI Practitioner?

To thrive as an Overnight AWS AI Practitioner, you need a solid background in cloud computing, machine learning principles, and proficiency with AWS services, often supported by certifications like AWS Certified Machine Learning – Specialty. Familiarity with tools such as Amazon SageMaker, AWS Lambda, and monitoring systems is typically required. Strong problem-solving skills, effective communication, and the ability to work independently during non-standard hours are valuable soft skills. These skills ensure high-quality deployment and maintenance of AI solutions, quick issue resolution, and seamless support for organizations operating around the clock.

What are some unique challenges of working as an Overnight AWS AI Practitioner, and how can they be managed?

Working overnight as an AWS AI Practitioner often involves supporting critical systems during off-peak hours, which can mean troubleshooting issues independently or responding to urgent incidents with limited immediate support from other teams. Adapting to a night schedule can be challenging, so maintaining a healthy work-life balance and establishing clear communication processes with daytime colleagues is essential. Successful practitioners proactively document their work, participate in handoff meetings, and utilize monitoring tools to ensure seamless operations and effective collaboration across shifts.

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

AspectOvernight Aws Ai PractitionerCloud Data Engineer
CertificationsAWS Certified Machine Learning – Specialty, AWS Certified Data Analytics – SpecialtyAWS Certified Data Analytics – Specialty, Google Cloud Professional Data Engineer
Work EnvironmentCloud-based AI projects, machine learning model deployment, data analysisData pipeline development, cloud infrastructure management, data integration
Industry UsageAI-focused roles in tech, finance, healthcareData infrastructure roles across various industries

The Overnight Aws Ai Practitioner primarily focuses on developing and deploying AI and machine learning models using AWS services, often working overnight shifts to support continuous deployment. In contrast, the Cloud Data Engineer concentrates on building and maintaining data pipelines and infrastructure. While both roles require cloud certifications and involve working with data, the AI Practitioner emphasizes AI/ML projects, whereas the Data Engineer focuses on data architecture and integration.

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Infographic showing various Overnight Aws Ai Practitioner job openings in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $112,339 per year, or $54 per hour.

AWS Certified AI Practitioner (Remote)

kgs

Nashville, TN • Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 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