Lead Software Engineer, Knowledge & AI Platform

Salesforce•San Francisco, CA

2d•Onsite

About The Position

Salesforce is seeking a Lead Member of Technical Staff (LMTS) to join the Service Cloud Engineering team. In this role, you will provide technical leadership and architectural direction across our core Knowledge product areas, including Self-Learning Knowledge (SLK) and other Core Knowledge Base domains the team owns. The Service Cloud Engineering team powers the core Knowledge product at Salesforce, serving over 12 million monthly active users. Our mission is to modernize the Knowledge experience by architecting deep integrations with Data Cloud, Einstein AI, and Agentforce — shaping the future of how knowledge is created, surfaced, and applied at scale.

Requirements

8+ years of software engineering experience with deep expertise in Java and object-oriented design patterns.
Proven ability to synthesize complex technical problems and product requirements into clear architectural paths and actionable strategic plans.
Proficiency in modern front-end development using JavaScript (ES6+), React, and related ecosystem tools (e.g., Redux, React Hooks, Next.js) to build responsive, scalable, and performant web applications.
Demonstrated success leading cross-team technical initiatives and influencing engineering decisions beyond the immediate team.
Strong written and verbal communication skills, with the ability to influence leadership and collaborate effectively with cross-functional stakeholders including Product Management, UX, and Architecture teams.
Experience building web-based solutions using web services and a proven ability to integrate with unfamiliar technologies quickly.
Bachelor's degree in Computer Science, Engineering, Management Information Systems (MIS), or equivalent practical experience.

Nice To Haves

Exposure to AI/ML technologies, such as large language models (LLMs), recommendation systems, or similar.
Experience with cloud-native and microservices architectures (e.g., Spring Boot, Guice, message queues, event-driven systems).

Responsibilities

Drive the architectural evolution and end-to-end delivery of core Knowledge features, including Self-Learning Knowledge (SLK) refactoring, SLK setup, and deep integrations with Data Cloud.
Design scalable foundational systems — such as Data Cloud orchestration frameworks and event-driven architectures — that can be adopted across multiple engineering organizations.
Take full ownership of product stability and customer success, leading critical production escalations, root cause analyses (RCAs), and resolving long-standing technical debt to unlock meaningful customer value.
Multiply the team's impact through technical coaching and mentorship of engineers at all levels (AMTS, MTS, SMTS), fostering a culture of high-standard code reviews and engineering excellence.
Champion Agile practices and continuous improvement, guiding the team toward clear milestones and technically sound incremental delivery in ambiguous environments.
Apply a strong foundation in service-oriented design, with a consistent habit of documenting and testing code and a focus on building reliable, scalable user experiences.