Senior AI Software Engineer

Company: CaptionCall, LLC

Job Title: Senior AI Software Engineer

Headquarter address: 4192 S. Riverboat Road, Salt Lake City, UT 84123.

Worksite address: Position is fully remote. Work from home benefit available.

To Apply: Please apply online at https://sorenson.com/company/careers/. Only qualified applicants should apply. Must have U.S. employment authorization. Do not apply if you are in F-1 or H-1 status or otherwise require employer sponsorship for U.S. employment authorization.

Job Duties:

• Deploy web applications and backend microservices in the JavaScript programming language hosted on Amazon Web Services (AWS).

• Deploy Automatic Speech Recognition (ASR) and other graphics processing unit (GPU)-based Machine Learning (ML) and Artificial Intelligence (AI) models to AWS cloud-based production Application Programming Interfaces (APIs).
• Design, implement, and deploy GPU-based microservice-based applications and APIs including REST, WebSocket, and gRPC.
• Design and implement high volume microservice data pipelines for real-time training of streaming AI models.
• Design and implement automated testing pipelines including writing unit tests using PyTest and JUnit, end-to-end tests, load tests using Locust, and A/B testing using LaunchDarkly.
• Design, implement, and optimize highly concurrent (multi-threaded and/or multi-process) object-oriented software libraries in the Java programming language.
• DevOps fundamentals including writing Infrastructure as Code Terraform scripts to deploy AWS services including VPC, subnets, security groups, NAT gateways, ECS, EKS, API Gateway, and Lambda.
• Design and implement API user authentication solutions using Auth0 and OAuth2.
• Design and build automatic Continuous Integration and Continuous Deployment (CI/CD) pipelines using GitHub Actions, Python scripts, and Linux operating system shell scripts.
• Decompose large projects and bug fixes into sprint goals and plan and track software releases and bugs/issues using Jira and GitHub.
• Develop Dockerfiles and deliver Docker images.
• Design and develop AWS monitoring tools using CloudWatch and Dynatrace dashboards to monitor software service health and performance.
• Deploy and maintain the stability of private (on-premises) and public cloud infrastructure for Kubernetes cluster based microservices.
• Collaborate with the Security Team and use security fundamentals and best practices to ensure environments and resources meet the company's minimum-security requirements.

• Design, implement, and manage both SQL and NoSQL databases.

Education: Master's degree in Computer Science, Computer Engineering, or related field.

Experience: 5 years of experience as a Software Engineer or closely related occupation.

Special Requirements (Skill Set):

Demonstrable knowledge of and prior experience in:

• Deploying GPU-based ML models to AWS cloud-based production systems.
• Python, Java, and JavaScript programming languages.
• Object-oriented software design and implementation.
• Private (on-premises) and public cloud infrastructure.
• Security fundamentals and best practices.
• Amazon Web Services (AWS)
• User Authentication using Auth0
• Linux operating system shell scripts.
• GPU based microservice design.
• High-volume real-time, streaming microservice system design.
• Developing Dockerfiles and delivering Docker images.
• Plan and track software release and bugs/issues using Jira and GitHub.
• Writing: testable code, unit tests using PyTest and JUnit, end-to-end tests, load tests using Locust, and A/B test using LaunchDarkly.
• Designing and building automatic CI/CD pipelines using GitHub Actions, Python scripts, and Linux operating system shell scripts.
• Designing, implementing, and managing both SQL and NoSQL databases.
• DevOps fundamentals including writing Infrastructure as Code scripts using Terraform.
• AWS networking infrastructure, including VPC, subnets, security groups, route tables, and NAT gateway.
• AWS CloudWatch and Dynatrace dashboard monitoring tools.
• Deploying ASR and other GPU-based ML and AI models to AWS cloud-based APIs.

Travel Requirements: No travel requirements.

Work Hours: 8:00 am - 5:00 pm, Monday - Friday.