Principal Full Stack Software Engineer, Salesforce

• 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
• 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

Desirable

• 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: 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 runbooks, 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
• 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. 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
• You'll join the established Event Monitoring team as it takes on a major new initiative, with a clear product vision, strong PM and design partnership, and meaningful technical headroom to set the long-term direction
• The work is visible, the customer impact is direct, and as the solution grows into a foundational platform across the organization, so does the leadership scope of this role

• End Date: September 30, 2026