Senior AI Software Engineer

Sorenson Communications; Salt Lake City (UT); Remote; USD 100,000 - 130,000; Full time

Job summary

A leading company is seeking a Senior AI Software Engineer to develop and deploy advanced AI and ML solutions on AWS. The role involves designing microservices, ensuring security compliance, and optimizing software performance. Ideal candidates will have a Master's degree and extensive experience in software engineering, particularly with AWS and GPU-based systems.

Qualifications

• 5 years of experience as a Software Engineer or closely related occupation.
• Demonstrable knowledge of deploying GPU-based ML models to AWS.

Responsibilities

• Deploy web applications and backend microservices on AWS.
• Design and implement high volume microservice data pipelines.
• Collaborate with the Security Team to ensure compliance.

Skills

Python

Java

JavaScript

Object-oriented software design

AWS

Linux operating system shell scripts

Security fundamentals

GPU based microservice design

CI/CD pipelines

SQL and NoSQL databases

Education

Master's degree in Computer Science

Tools

Terraform

Docker

Jira

GitHub

CloudWatch

Dynatrace

Job description

Description

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.

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

This employer is required to notify all applicants of their rights pursuant to federal employment laws.
For further information, please review the Know Your Rights notice from the Department of Labor.