Principal Software Engineer, Full Stack (Observability)

Salesforce•San Francisco, CA

2d•Hybrid

About The Position

Salesforce is seeking a Principal Software Engineer, Full Stack (Observability) to join the Trusted Services organization, specifically the Event Monitoring team. This team is building a unified platform for metrics, logs, and traces across Salesforce, aiming to provide customers with a single place to troubleshoot and understand behavior across multiple services. The role involves a major new initiative with opportunities to shape architecture, data models, customer experience, and team evolution. The team utilizes an AI-first engineering strategy, integrating AI assistants throughout the development lifecycle for tasks like scaffolding services, generating tests, drafting migrations, reviewing code, and debugging. Engineers are expected to use AI coding assistants, drive design conversations with AI, build internal tooling, and develop judgment in using AI effectively. The role is visible, has direct customer impact, and offers leadership scope as the solution grows into a foundational platform.

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.