Lead Backend Engineer - AI-Driven, Scalable APIs

salesforce.com, inc.; San Francisco (CA); On-site; USD 173,000 - 260,000; Full time

Job summary

Salesforce is seeking a Backend Software Development Engineer to join a world-class team building scalable backend services, APIs, and data processing pipelines for multiple clouds and customer workloads.

You will work with AI-driven features, adhere to high-quality coding standards, participate in agile practices, and contribute to the shared system context enabling reliable AI-powered deployments.

Qualifications

• 3+ years backend software development experience.
• Deep knowledge of object oriented programming languages: Java, C++, Go, C#, Ruby, Scala, Python, Node.JS, or JavaScript.
• Broad knowledge of web standards relating to APIs such as REST, SOAP, XML, WSDL, HTTP, JSON, etc.
• Experience with Spring, gRPC, REST and the HTTP protocol.
• Experience with Agile development methodology.
• A demonstrated, genuine AI-first approach to engineering and using AI tools in workflows.
• Advanced prompt engineering skills for reliable AI outputs.

Responsibilities

• Backend application development for Marketing/Commerce/Sales/Big Data/Service/Einstein/MuleSoft/Platform/Industries Clouds/Slack and Heroku.
• Design, implement, and tune robust APIs and API framework features for multi-tenant environments.
• Experience handling large data sets in the cloud (e.g., AWS, GCP, Azure).
• Integration with internal/external systems and CI/CD practices.
• Build and ship high-quality, production-grade software with AI as a core part of development workflow.

Skills

Backend development

Java

Python

JavaScript/Node.js

REST APIs

Education

Related technical degree

Job description

Salesforce is seeking a Backend Software Development Engineer to join a world-class team building scalable backend services, APIs, and data processing pipelines for multiple clouds and customer workloads.

You will work with AI-driven features, adhere to high-quality coding standards, participate in agile practices, and contribute to the shared system context enabling reliable AI-powered deployments.