Value Acceleration Engineer LMTS

Salesforce•San Francisco, CA

6d•Hybrid

About The Position

Salesforce is seeking a Value Acceleration Engineer to join their AI Labs team. This role focuses on building and deploying AI agents that can reliably operate enterprise software like SAP, Oracle, and Workday. The team operates like a startup within Salesforce AI Labs, offering autonomy and the resources of a large company. The Value Acceleration Engineer will work directly with customers to integrate AI agents into their business processes, write custom code, debug issues, and contribute to product development based on deployment learnings.

Requirements

You can write and debug JavaScript or TypeScript and reason about web applications, APIs, and data flow.
You enjoy working directly with users: asking precise questions, building alongside them, and explaining technical problems clearly.
You’ve led complex customer-facing deployments and built tools or practices that improved outcomes beyond your own projects.
You can align stakeholders on when to extend the product, narrow scope, or stop an unsafe rollout.
8+ years of relevant experience.

Nice To Haves

Playwright, browser automation, browser extensions, RPA, or enterprise integration.
Agent systems, tool execution, evaluations, or failure recovery.
SAP, Oracle, Workday, Salesforce, or similarly complex enterprise applications.
Forward-deployed engineering or customer-facing product development.

Responsibilities

Build Directly With Customers: Work with process owners and customer IT to select workflows, define success, and secure the test access and data needed to build. Run hands-on sessions that help customers use the product themselves, with clear scope and readiness expectations. Help customers understand where the product can deliver value, explain its capabilities and limitations clearly, and connect technical results to business outcomes.
Engineer Reliable Automation: Write custom JavaScript tools when existing capabilities cannot complete a task. Debug failures across browser behavior, agent execution, application state, and backend services. Build tests for business outcomes, exceptions, partial completion, and recovery. Help launch and stabilize workflows, documenting monitoring and recovery procedures and establishing support ownership with the team.
Make the Next Deployment Easier: Turn deployment lessons into reusable tools and tests, and work with core engineering to address recurring product gaps. Use AI development tools thoughtfully while remaining accountable for code quality, security, and maintainability.