Application Engineer, Salesforce

The Sales & Marketing Intelligence team enables business teams across Meta products including Workplace, Audience Network, Meta Reality Labs, and Media Partnerships. The team’s processes range from prospect acquisition to optimizing customer growth. We strive in our vision to make Sales & Marketing Teams better at what they do by automating their processes, building integrations, and providing personalized recommendations.

Responsibilities

• Technical ownership of projects and managing resources
• Work with product managers to drive strategic value through custom applications built on Salesforce, as well as our internal software stack
• Architect highly available, scalable, and secure systems
• Comply with change management policies to ensure data integrity and system stability
• Define and track performance metrics to measure business value and inform technical decisions
• Build interfaces for complex systems and high-quality tools

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 5+ years of experience developing business applications in Salesforce, PHP, Java, C++, Python, or similar
• 5+ years of experience with Salesforce Web Services APIs like SOAP and REST-based Web Service APIs, the Bulk API, and the Metadata API
• 3+ years of experience in Visualforce/Lightning Web Components/Apex incorporating JS frameworks like React, Bootstrap or Angular Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Platform Developer II certification
• Experience applying UI/UX design principles to build user-facing features or tools
• Experience building on MuleSoft
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience owning projects from end-to-end
• SQL experience in handling volumes of data, performance tuning
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience in understanding code bases, including API design techniques
• Expertise with data management: structured and unstructured DBs, SQL and RDBMS technologies, SOA design principles
• Experience building and supporting production quality software

Preferred qualifications

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Platform Developer II certification
• Experience applying UI/UX design principles to build user-facing features or tools
• Experience building on MuleSoft
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience owning projects from end-to-end
• SQL experience in handling volumes of data, performance tuning
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience in understanding code bases, including API design techniques
• Expertise with data management: structured and unstructured DBs, SQL and RDBMS technologies, SOA design principles
• Experience building and supporting production quality software