Software Engineering PMTS

Salesforce•San Francisco, CA

15h•Remote

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Agentforce is the future of AI, and you are the future of Salesforce. The Trusted Services organization builds the security, resilience, and data governance capabilities that thousands of customers rely on every day. Our Event Monitoring team is building on its deep foundation in event data to deliver a single, coherent platform for metrics, logs, and traces across Salesforce. Our charter is to give customers one place to troubleshoot and reason about behavior across multiple services. You'll be joining an established team as it takes on a major new initiative, with room to shape the architecture, the data model, the customer experience, and how the team evolves. Unified Observability 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, drive design conversations with AI in the loop, build internal tooling and agents that automate repetitive engineering work, develop strong judgment about when to lean on AI and when to slow down, and 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 product requirements into parallel engineering workstreams and drive execution across a small team.
Full-stack engineering ability: deep proficiency in Java (strong API design, data modeling, and service-layer architecture), plus hands-on front-end/UI development experience building modern web interfaces with frameworks such as React or Lightning Web Components (LWC).
Demonstrated experience operating distributed, multi-tenant systems at scale, with hands-on knowledge of observability and streaming systems such as OpenTelemetry, Kafka, and large-scale telemetry stores (HBase, ClickHouse, or equivalent time-series databases), and dashboarding with Grafana.
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 observability, monitoring, telemetry pipelines, SRE/on-call tooling, or incident response systems.
Familiarity with OpenTelemetry and OCSF standards
Experience with the OpenTelemetry ecosystem (collectors, semantic conventions, instrumentation libraries) and query languages such as PromQL.
Familiarity with high-cardinality metrics, distributed tracing, and log aggregation at scale.
Experience building data-visualization and dashboard UIs — charts, time-series views, and interactive query experiences for large telemetry datasets.
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 data ingestion, query performance, and cost boundaries.
Define how Unified Observability cleanly integrates with existing products and telemetry sources: instrumentation standards, data onboarding, access control, and a graceful path from per-team tooling to a shared platform.
Use AI tools throughout your day, for code generation, refactoring, test authoring, code review, and investigation.
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.