Software Engineer - AI & Data Operations

About OpenSesame

OpenSesame's mission is to help develop the world's most productive and admired workforces. We do this by delivering a comprehensive catalog of elearning courses from the world's top publishers. We add value to customers through their entire learning journey.

While it appears to most people that we just sell training courses (over 40,000 of them), what we really offer is the opportunity for companies to upgrade the skills of each of their employees.

We are at a pivotal time in our growth as we diversify the ways we drive revenue. We've expanded our product offering dramatically, and have a growing network of partners that is developing into a vibrant channel. Our customer base has high satisfaction ratings and there is room to grow our retention even more.

www.opensesame.com/about.

About the Team

Our AI and Data Operations team is at the forefront of driving efficiency and innovation across OpenSesame. We work in an agile, continuously improving environment, always seeking new ways to optimize our processes and empower our colleagues through cutting-edge automation solutions. The team currently includes two data analysts responsible for the ETL pipeline, and this role will complement their efforts in building out AI-powered automation solutions.

About the Job

As an Automation Engineer on the AI and Data Operations team, you will develop and maintain modular tools that help non-technical employees automate tasks, boosting productivity across departments like Sales, Marketing, and Finance.

Initially, you'll build proof-of-concept Retrieval-Augmented Generation (RAG) workflows for internal use cases, then expand into AI and related areas to address further needs. Ultimately, you'll create and refine a reusable component library that powers our AI-driven automation system, using TDD and CI/CD principles to ensure agility and minimize toil.

Performance Objectives

30 days: 

• Leverage your existing deep understanding of Generative AI operations and adjacent technologies to Deploy a Proof-of-Concept AI building block for internal use.

60 Days:

• Build out additional AI building blocks for internal use.
• Test and deploy a system to maintain and update AI building blocks.

90 Days:

• Optimize the CI/CD pipeline for faster, more reliable software delivery.
• Begin automating infrastructure provisioning using tools like Terraform.
• Strengthen monitoring and achieve 99.9% uptime for automation APIs.

6 Months:

• Build a reusable library of AI …