Lead Software Engineer, Success & Finance Platform

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Applications will be accepted until 05/31/2026.

Job Category:
Software Engineering

Company:
Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action, tech meets trust, and innovation isn’t a buzzword—it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

The Employee Success & Finance Platform team builds and maintains the integration backbone that connects Salesforce's most sensitive enterprise systems—HR, payroll, ERP, and Finance. As the Lead Software Engineer on this team, you'll set the technical direction for how data moves securely, accurately, and resiliently across our SaaS ecosystem. This is a high‑impact role for an engineer who thinks in platforms, not just features—someone who cares deeply about data integrity, observability, and building systems that scale with the business.

You'll partner directly with HR and Finance leadership to shape the technical roadmap, and you'll lead a team that takes ownership of engineering quality from architecture to production.

• Define the integration architecture for complex, high‑stakes data flows between HR, ERP, and third‑party SaaS providers—designing for reliability, auditability, and scale.
• Build and maintain validation frameworks that ensure source of truth data stays consistent as it moves across enterprise systems, with automated reconciliation to catch failures before the business does.
• Drive observability across the platform by implementing comprehensive telemetry (logs, metrics, traces) so the team has full visibility into system health at all times.
• Lead and mentor a platform engineering team, setting standards for code quality, design patterns, and technical documentation—and fostering a culture of Engineering Excellence.
• Own the Dev Ops and testing strategy, including CI/CD pipelines, unit/integration/E2E test coverage, and a proactive approach to technical debt.
• Translate business requirements into technical roadmaps in close partnership with HR and Finance stakeholders, ensuring engineering decisions are grounded in real business impact.
• Design for agentic systems—build the tooling and guardrails needed for autonomous agents to safely navigate sensitive financial and HR data, including payroll adjustments and budget reconciliation workflows.
• Ensure GenAI data readiness by making HR policies and financial records accessible to agents while maintaining strict PII/SPII masking and data sovereignty standards.

• 10+ years of software engineering experience, including at least 2 years in a technical lead, staff, or equivalent senior scope role.
• Deep experience designing and building SaaS‑to‑SaaS integrations, including custom middleware and APIs that bridge legacy and modern enterprise systems.
• Demonstrated track record of handling high‑stakes data—Finance and HR experience especially valued, where data accuracy is non‑negotiable.
• Strong observability mindset: you instrument everything and treat monitoring as part of the definition of done.
• Platform‑oriented thinking: you build for reusability, documentation, and the productivity of the broader engineering org.
• Working knowledge of SOX compliance and PII/SPII data classification.
• Strong communication skills—you can translate complex technical concepts for non‑technical stakeholders and build alignment across teams.
• A related technical degree required.

• Experience with Workday (Extend, Orchestration, Integration Studio, or Studio).
• Background in Fin Tech or a highly regulated industry where audit trails and compliance are core to the engineering process.
• Hands‑on experience building or operating production‑grade AI/ML or agentic systems, with attention to data cleanliness, prompt reliability, and…