Software Engineering PMTS

Salesforce•San Francisco, CA

7d•$197,300 - $344,700

About The Position

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. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. At Salesforce, trust is our #1 value, and the Trusted Services organization builds the security, resilience, and data governance capabilities that thousands of customers rely on every day. We're standing up a new engineering team to deliver Trusted Services Lite (TS Lite), a simplified, SMB-friendly version of our enterprise-grade Trusted Services suite. Our charter is to make critical data protection accessible to customers who don't have dedicated security teams, while building a clear path to the full Trusted Services portfolio as their needs grow. You'll be joining at the ground floor, shaping the architecture, the customer experience, and the team culture itself. AI-First TS Lite is being built with an AI-first engineering strategy. AI assistants are core to how we design, write, review, test, and operate our software. Engineers on this team are expected to: * Use AI coding assistants throughout the development lifecycle: scaffolding services, generating tests, drafting migrations, reviewing diffs, and debugging production issues * Drive design conversations with AI in the loop — exploring tradeoffs, generating alternatives, and stress-testing assumptions before committing to an approach * Build internal tooling and agents that automate repetitive engineering work (PR triage, on-call run books, log analysis, capacity planning) * Develop strong judgment about when to lean on AI and when to slow down - verifying generated code, catching subtle hallucinations, and owning the final result * Share patterns, prompts, and workflows that make the rest of the team faster We're looking for engineers who are genuinely curious about AI as a craft tool and want to push the boundary on what an AI-augmented team can ship.

Requirements

10+ years of software engineering experience, with 3+ years in a technical leadership or principal-level role.
Hands-on experience with Claude Code or similar agentic coding environments.
Comfort using AI assistants in your engineering workflow, with judgment about where they accelerate the work and where careful human review is still essential.
Ability to decompose ambiguous product requirements into parallel engineering work-streams and drive execution across a small team.
Deep proficiency in Java with strong API design, data modeling, and service-layer architecture skills.
Demonstrated experience operating distributed, multi-tenant systems at scale, with hands-on knowledge of storage and streaming systems such as HBase, Kafka, or equivalents.
A collaborative, low-ego working style. You write clearly, ask good questions, and build consensus around the right technical direction without needing to win every debate.
A bias toward measurable customer outcomes and a willingness to be accountable for them.

Nice To Haves

Background in security, audit, observability, compliance domains, audit logging, or data retention systems.
Familiarity with Salesforce platform internals: permissions, licensing, packaging, or Shield products.
Experience leading technical strategy across platform and product organizations, including capacity planning and cross-team dependency management.
A track record of mentoring senior engineers and shaping engineering culture at team or org scale.

Responsibilities

Work closely with Product Management to align and steer cross-functional architectural decisions.
Lead the technical design and end-to-end delivery of features, from architecture to production operation.
Drive cross-team alignment with partners on capacity, retention, scale, and performance boundaries.
Define how TS Lite cleanly coexists with existing products: licensing, permission gating, upgrade and downgrade flows, and graceful evolution into the full Trusted Services suite.
Use AI tools throughout your day, for code generation, refactoring, test authoring, code review, and investigation. We expect AI use to be part of how the work gets done, not an afterthought, and we look to senior engineers to model what great AI-assisted engineering looks like.
Raise the engineering bar across the team through technical mentorship, design reviews, and clear written communication.
Help shape team practices, hiring, and engineering culture as the team scales.