Lead Software Engineer (Knowledge & AI Platform)

Role Overview

Join Salesforce as a Lead Software Engineer on the Service Cloud Engineering team. You’ll provide technical leadership and architectural direction for the core Knowledge product areas (including Self-Learning Knowledge (SLK)), driving end-to-end delivery of key features and designing scalable foundational systems.

Key Missions / Responsibilities

• Provide technical leadership and architectural direction across core Knowledge product areas (including SLK).
• Drive architectural evolution and end-to-end delivery of Knowledge features, including:
  • SLK refactoring
  • Deep integrations with Data Cloud
• Own product stability and customer success:
  • Lead critical production escalations
  • Run root cause analyses
  • Resolve long-standing technical debt
• Mentor engineers at all levels and champion Agile practices.
• Apply a strong foundation in service-oriented design.

Requirements

• 8+ years of software engineering experience with deep expertise in Java and object-oriented design patterns.
• Proven ability to lead cross-team technical initiatives and influence engineering decisions beyond your immediate team.
• Strong communication skills to collaborate with Product Management, UX, and Architecture teams.
• Ability to translate complex technical and product requirements into clear architectural plans.
• Experience building web-based solutions using web services, with the ability to integrate with unfamiliar technologies quickly.
• Modern front-end proficiency using JavaScript (ES6+), React, and related ecosystem tools (Redux, React Hooks, Next.js).
• Experience with cloud-native and microservices architectures, including technologies such as:
  • Spring Boot
  • Guice
  • Message queues and event-driven systems
• Exposure to AI/ML technologies, such as large language models (LLMs) and recommendation systems.

Nice-to-Haves

• Prior experience integrating AI/ML capabilities into production customer-facing systems (e.g., LLM-powered or recommendation-based Knowledge features).
• Demonstrated success refactoring and evolving large-scale, service-oriented platforms.