AWS Certified AI Practitioner (Remote)
- Source: LinkedIn
- Koniag Government Services
- Remote
- Nashville
- Full-Time
- Mid level
Job Description
This position may be filled prior to the posted deadline. Interested candidates are encouraged to apply as soon as possible.
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 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 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.
Benefits include medical, dental, and vision insurance, 401(k) retirement plan, paid time off, paid parental leave, life and disability insurance, flexible spending accounts, commuter benefits, and tuition reimbursement.
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 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 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 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 effect…
Skills
- amazon-web-services
- amazon-connect
- amazon-lex
- amazon-polly
- polly
- amazon-comprehend
- amazon-rekognition
- amazon-transcribe
- amazon-sagemaker
- bedrock
- streamline
- aws-lambda
- amazon-eventbridge
- aws-step-functions
- serverless
- ramp-com
- aws-govcloud
- aws-managed-services
- amazon-machine-learning
- amazon-text-to-speech
- amazon-sagemaker-pipelines
- Python
- aws-iam
- microsoft-excel
- microsoft-powerpoint
- microsoft-outlook
- microsoft-teams
- microsoft-sharepoint
- d3
- aws-glue
- amazon-kinesis
- amazon-redshift
- Tensorflow
- PyTorch
- Scikit-learn
