Principal Backend Software Development Engineer, Agentforce for Supply Chain

Overview of the Role Global supply chains still rely on slow, manual processes – email, spreadsheets, and fragmented data. The economy moves fast but supply chains don’t, creating an inefficiency that affects the $13T of goods shipped annually and is one of the largest untapped opportunities in modern enterprise. Agentforce for Supply Chain is reimagining the supply chain with an AI-powered platform for designing, automating, and running end‑to‑end business processes, with seamless collaboration through familiar channels like email. For Salesforce, this represents a massive growth opportunity in the back office, with innovations that flow into the front office. Customers are clamoring for more, rapidly expanding their use cases as we enter an exhilarating growth phase. We are seeking a highly experienced and impactful Lead Member of Technical Staff (LMTS) or Principal Member of Technical Staff (PMTS) to serve as a key individual contributor within the Integration & Platform team. This role is crucial for designing, building, and scaling the mission‑critical data and integration backbone of our platform. The ideal candidate will possess deep expertise in building robust, scalable data ingestion and export pipelines, integrating custom services with enterprise platforms, and simplifying complex customer APIs. Key Focus Areas Platform Integration: Architecting and implementing powerful integrations between our core platform and Salesforce ecosystem products, specifically Mulesoft and Flow. Data Export & Scale: Leading the design and implementation of highly scalable, efficient, and reliable data export pipelines. This includes integrating our internal data sources (CSV files, REST API outputs) with Salesforce Data Cloud and/or Informatica. ETL Automation & Reliability: Optimizing our existing ETL pipeline infrastructure to support a daily, self‑serve customer data synchronization mechanism with Data Cloud. This solution must be fully automated, requiring minimal engineering involvement post‑initial setup, and demonstrate exceptional robustness, scalability, reliability, and performance. Customer API Abstraction: Designing and building simplified, performant, customer‑facing APIs and webhooks. This includes creating an abstracted version of high‑value functionality currently exposed via complex GraphQL API endpoints, focusing on a minimal, simplified interface for core customer workflows. Distributed Systems Expertise: Deep understanding and practical experience with event queues, asynchronous task processing, and designing highly available, geographically distributed systems. Responsibilities 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 integration initiatives. Conduct thorough code reviews and mentor other engineers on best practices for performance, security, and scalability. Collaborate cross‑functionally with Product Management and other engineering teams to define requirements and deliver solutions that meet business needs. Build and ship high‑quality, production‑grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high‑quality code. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably. Critically evaluate code (Human or AI‑generated) for correctness, quality, security, and performance. Long‑Term Goals & Strategic Impact Set the technical direction and standards for all data integration and ETL processes within the platform. Identify and mitigate architectural risks associated with scaling our data infrastructure to support exponential customer growth. Drive continuous improvement in system performance, observability, and operational efficiency. Experience Gained & Impact Made Experience Gained: The candidate will gain unparalleled experience leading the transformation of mission‑critical data systems at enterprise scale, directly influencing the architecture of Salesforce’s next‑generation integration platform utilizing tools like Mulesoft and Data Cloud. Impact Made: This role is critical to enabling customer success by ensuring a reliable, performant, and autonomous data sync experience. The work directly forms the foundational data layer powering core customer intelligence and platform functionality. Required Qualifications 8+ years of professional software development experience, with a significant focus on large‑scale data systems, ETL, or integration platforms. A related technical degree required. 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 building and operating distributed systems, concurrency, and high‑availability architectures. 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. 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) in development workflows. Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production‑ready. Preferred Qualifications 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. Advanced degree in Computer Science or a related technical field. Published works including contributions to open‑source projects, patents, or papers. Exposure to the supply chain, logistics, or manufacturing industry. Accommodations If you need a reasonable accommodation during the application or the recruiting process, please submit a request via the Accommodations Request Form. Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Benefits Salesforce offers a variety of benefits to help you live well, including time‑off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. In addition, compensation will be determined by location, job level, experience, and may include incentive compensation, equity, and benefits. #J-18808-Ljbffr