Principal Software Engineer, Agentforce for Supply Chain

Salesforce•Seattle, WA

2d•Hybrid

About The Position

Salesforce is seeking highly experienced Senior, Lead, and Principal Engineers to join the Agentforce for Supply Chain teams. Agentforce is reimagining the supply chain with an AI-powered platform for designing, automating, and running end-to-end business processes. This role offers a significant growth opportunity in the back office, with innovations that flow into the front office. The Super Agent team focuses on the operational heart of Agentforce, managing complex state transitions and interfaces. The Integration & Platform team owns the data and integration backbone, connecting the platform to the broader Salesforce ecosystem and powering self-serve data synchronization. This is a technically challenging and impactful role with wide autonomy, real ownership, and meaningful advancement.

Requirements

3+ years (Senior), 5+ years (Lead), 8+ years (Principal) of industry experience as a backend engineer, building and operating large-scale, user-facing web applications and/or data systems.
A related technical degree required.
Deep expertise in multiple areas of backend engineering: data modeling, DB performance tuning, state management, API design, transactionality, concurrency, fault tolerance, and scaling.
Demonstrated expertise in designing, building, and maintaining production-grade data pipelines (ETL/ELT).
Expert-level proficiency in at least one modern programming language (e.g., Java, Python, Go) suitable for platform development.
Proven experience designing and implementing robust, external-facing REST APIs and Webhooks.
Deep practical knowledge of distributed systems, high-availability architectures, event queues, and asynchronous task processing.
Track record of diagnosing systemic architectural problems, prioritizing across competing technical investments, and driving measurable improvement over time.
Experience designing and improving interfaces and boundaries between teams and systems.
Experience in a lead technical role (LMTS/PMTS level or equivalent), driving and owning complex projects as an individual contributor.
Excellent written and verbal communication skills, with the ability to lead real-time technical design discussions.
Experience working in tandem with Product Managers and Engineers to shape requirements, evaluate tradeoffs, and balance product delivery against foundational investment.
A demonstrated, genuine AI-first approach to engineering — using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows.
Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate system context that makes AI outputs reliable, secure, and production-ready.

Nice To Haves

B.S. in Computer Science (M.S. preferred)
Mastery of Golang, GraphQL, and PostgreSQL
Hands-on experience with Salesforce integration technologies such as Mulesoft or Salesforce Data Cloud
Experience working with large-scale event streaming platforms (e.g., Kafka, Kinesis)
Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes)
Experience designing or working with GraphQL API implementations
Experience with workflow engines
Exposure to the supply chain, logistics, or manufacturing industry
Experience working within rapidly evolving systems, balancing early-stage ambiguity with scaling, reliability, and maintainability concerns
Notable open-source contributions, patents, or published research
Familiarity with the Salesforce platform

Responsibilities

Diagnose and prioritize foundational investments across the Super Agent backend, partnering with engineering leadership.
Own cross-cutting system problems, from architectural decomposition to cross-team interface design.
Build shared understanding of system health and risk, establishing frameworks and observability.
Raise and maintain the engineering quality bar through pragmatic standards and team practices.
Architect and implement integrations between the core platform and Salesforce ecosystem products (Mulesoft, Flow).
Lead the design and implementation of scalable, efficient, and reliable data export pipelines.
Optimize existing ETL pipeline infrastructure for daily, self-serve customer data synchronization.
Design and build simplified, performant, customer-facing APIs and webhooks.
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.
Conduct thorough code reviews and mentor engineers on best practices.
Collaborate cross-functionally with Product Management and other engineering teams.
Build and ship production-grade software using modern engineering practices, with AI as a core part of the development workflow.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows.
Contribute to building and maintaining shared system context for AI operation.
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Mentor engineers as a senior peer and force multiplier.
Set the technical direction and standards for data integration, ETL processes, and backend architecture.
Identify and mitigate architectural risks associated with scaling data infrastructure.
Drive continuous improvement in system performance, observability, and operational efficiency.