Senior/Lead Quality Engineer - AI Platform

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Job Category

Software Engineering

Job Details

About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

About the organization:

Einstein products & platform democratize AI and transform the way our Salesforce Ohana builds trusted machine learning and AI products - in days instead of months. It augments the Salesforce Platform with the ability to easily create, deploy, and manage Generative AI and Predictive AI applications across all clouds. We achieve this vision by providing unified, configuration-driven, and fully orchestrated machine learning APIs, customer-facing declarative interfaces and various microservices for the entire machine learning lifecycle including Data, Training, Predictions/scoring, Orchestration, Model Management, Model Storage, Experimentation etc.

We are already producing over a billion predictions per day, Training 1000s of models per day along with 10s of different Large Language models, serving thousands of customers. We are enabling customers' usage of leading large language models (LLMs), both internally and externally developed, so they can leverage it in their Salesforce use cases. Along with the power of Data Cloud, this platform provides customers an unparalleled advantage for quickly integrating AI in their applications and processes.
 

About the team:

Join the AI Platform Quality Engineering team, and become a specialist on Salesforce's AI Platform! You'll get to work with latest technology in the AI space (including generative AI), and collaborate with the team and cloud to identify and run quality initiatives to support massive scale planned for this year. We are a small, friendly team that has been working together for 3+ years - outside of quality, we focus on volunteering and shared interests such as gardening!
 

Job description summary:

As a Quality Engineer for the Salesforce AI platform, you will be responsible for designing and driving the implementation of comprehensive test plans/quality strategies. You will collaborate closely with engineering teams to ensure the successful execution of tests and maintain high FIT test pass rates in various environments. You’ll learn about the E2E workings of the platform and write integration tests to cover critical areas for traditional and generative AI flows. You’ll have the opportunity to enhance our test frameworks, work on test environment stability, and develop automation strategies.

Skills needed for role:

• A related 4-year technical degree required

• Test Gap Analysis & Coverage: Experience analyzing coverage gaps and writing E2E and integration tests, partnering with teams to drive service level test coverage

• Technical Expertise: Technical excellence and leadership required to learn a new platform and drive end to end test strategy for it, partnering with Quality Engineering team, Hawking scrum teams and customer cloud Q3s to implement.

• Cross Team Collaboration: Ability to work with stakeholders (internal customers) from multiple organizations that leverage our central platform for custom applications. Collaborate with them to determine key shared usage patterns to prioritize test coverage of, as well as provide guidance to these customers on how to proactively test their application’s integration with the platform.

• Experience with Java/Python

• Experience with test runners and configuration

• Extensive experience debugging systems

• 6+ years of QE experience and 2+ years of experience leading projects and partnering/leading jr members of the team.

Nice to have skillsets (or skillsets expect to develop in this role):

• Understanding of LLM Model hosting with Sagemaker

• Understanding LLM Finetuning and Inferencing

• Testing integrations with Cohere, Anthropic, Dolly, Google, etc. as well as internal models

• Sagemaker GroundTruth integration for data labeling, Bedrock for model serving

• Experience with Azure Open AI

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