Senior/Lead/Principal Software Engineer, Agentforce Supply Chain
Listed on 2026-05-05
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Software Development
Software Engineer, Cloud Engineer - Software, Software Architect, Backend Developer
Location: New York
Job Category
Software Engineering
About the OpportunitySalesforce’s Agentforce for Supply Chain is an AI‑powered platform that designs, automates, and runs end‑to‑end business processes with seamless collaboration through familiar channels like email. The role is focused on delivering scalable, high‑reliability technology that powers the front‑ and back‑office of the platform.
The Teams Super Agent TeamThe Super Agent backend is the operational heart of Agentforce for Supply Chain. It manages complex, infinitely configurable state, state transitions, and interfaces across the platform. The team is hardening and scaling its foundations to support accelerating customer adoption.
Integration & Platform TeamThe Integration & Platform team owns the mission‑critical data and integration backbone of the platform. It designs, builds, and scales systems that connect the platform to the broader Salesforce ecosystem, including Mule Soft, Flow, and Data Cloud, and powers the self‑serve data synchronization mechanisms that customers rely on daily.
What You’ll DoWe are seeking senior, lead, and principal engineers to serve as key individual contributors across the Super Agent and Integration & Platform teams. You will own the hardest cross‑cutting system problems, set technical direction, and drive foundational investments that enable Agentforce for Supply Chain to scale.
Super Agent Responsibilities- Diagnose and prioritize foundational investments across the backend, partnering with engineering leaders to sequence them against product delivery.
- Own the hardest cross‑cutting system problems, from architectural decomposition to cross‑team interface design, and engage hands‑on when required.
- Build shared understanding of system health and risk, establishing frameworks and observability to drive confident investment decisions.
- Raise and maintain the engineering quality bar through pragmatic standards, guardrails, and team practices that prevent regressions and keep code healthy over time.
- Architect and implement powerful integrations between the core platform and Salesforce ecosystem products, specifically Mule Soft and Flow.
- Lead the design and implementation of highly scalable, efficient, and reliable data export pipelines, integrating internal data sources with Salesforce Data Cloud and/or Informatica.
- Optimize existing ETL pipeline infrastructure to support a daily, self‑serve customer data synchronization mechanism that requires minimal engineering involvement after setup.
- Design and build simplified, performant, customer‑facing APIs and webhooks, including an abstracted version of high‑value functionality currently exposed via complex Graph
QL endpoints.
- Architect, design, and deliver high‑quality, scalable code for complex data integration and platform features.
- Drive technical decision‑making and project execution as the primary individual contributor for key initiatives.
- Conduct thorough code reviews and mentor engineers on performance, security, and scalability best practices.
- Collaborate cross‑functionally with Product Management and other engineering teams to define requirements and deliver solutions that meet business needs.
- Build and ship production‑grade software using modern engineering practices with AI as a core part of your workflow.
- Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows.
- Contribute to building and maintaining shared system context—a repository of system designs, constraints, and standards that enable AI to operate accurately and reliably.
- Critically evaluate code—human or AI‑generated—for correctness, quality, security, and performance.
- Mentor engineers as a senior peer and force multiplier, shaping stronger engineering judgment and a higher‑performing team.
- Set the technical direction and standards for data integration, ETL processes, and backend architecture across the platform.
- Identify and mitigate architectural risks associated with scaling our data infrastructure to support exponential customer growth.
- Drive continuous improvement in system performance,…
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