Application Engineer
Posted 8 Jul 2026
Advertised as “Application Engineer (AI Automation)”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- People management
No salary listed for this role.
Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem.
This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us.
As an Application Engineer for AI Automation, you will be at the clinical edge of our intelligence layer. This isn't just about writing code; it's about architecting the nervous system of our automated enterprise. You will bridge the gap between heavy-duty enterprise platforms (Salesforce, Zuora, ServiceNow) and the next generation of Agentic AI.
Your primary mission will be building high-performance Model Context Protocol (MCP) servers that allow AI agents to interact deeply with complex business logic—specifically within the Salesforce ecosystem (Quote, Opportunity, and Renewal services). You’ll move from building RAG-based retrieval to orchestrating Agent-to-Agent communication, creating a seamless autonomous workflow across our tech stack.
Key Responsibilities
- Architect MCP Servers: Design and implement robust MCP servers to expose Salesforce services (Quote, Opportunity, Renewal) and other core platforms to AI agents.
- Data Model Synthesis: Rapidly decompose the data models of enterprise applications like Zuora, Salesforce, and ServiceNow to build effective schemas for AI interaction.
- Build AI Pipelines: Develop and optimize Retrieval-Augmented Generation (RAG) workflows and AI agents that can execute complex tasks with minimal human intervention.
- Agentic Orchestration: Lead the transition from simple chatbots to Agentic AI, focusing on multi-agent collaboration and autonomous "Agent-to-Agent" communication.
- Integration Engineering: Build and maintain secure, scalable integrations using REST APIs across disparate cloud environments.
- Technical Leadership: Act as a subject matter expert for AI automation, guiding the evolution of our automation strategy and mentoring junior engineers.