Senior​/Lead Software Engineer; Developer Productivity; Artificial Intelligence Tooling

Job Responsibilities

• The AI Solutions team in Technology & Product builds internal products and platforms that help Salesforce engineers adopt AI-assisted development safely, effectively, and measurably
• Our work spans developer experiences, AI usage and outcome intelligence, governance, telemetry, and integrations with coding tools and engineering systems
• As a Lead Member of Technical Staff, you will design, build, and own full-stack product and platform capabilities across desktop applications, backend services, data pipelines, dashboards, and developer-facing integrations
• You will help turn fast-moving AI developer productivity ideas into reliable software that thousands of Salesforce engineers can use every day
• Lead the technical design and delivery of complex, cross-cutting capabilities across internal developer-productivity products, spanning desktop experiences, backend services, data and analytics platforms, governance workflows, and integrations with AI coding tools and engineering systems
• Build backend APIs, data models, ingestion flows, dashboards, and user experiences that connect AI tool usage to outcomes engineers and leaders can act on
• Set technical direction for a product or platform area, translating ambiguous requirements into design specifications, test strategies, and incremental delivery plans; partner with product and engineering stakeholders to shape medium-term priorities and validate feasibility
• Define and raise the operational bar across the systems you lead by establishing telemetry, SLIs and SLOs, controlled rollout strategies, playbooks, and long-term ownership practices; lead incident investigation and root‑cause analysis when needed
• Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code
• Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale
• Establish and curate the shared system context - designs, constraints, standards, operational knowledge, and decision records - that helps both engineers and AI agents operate accurately and reliably
• Raise the team’s technical quality through design and code reviews, coaching, pairing, and clear definitions of done; delegate appropriately while remaining accountable for the overall technical outcome

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year

• Ability to explain initiatives and designs clearly to engineers, product partners, and engineering leadership; make sound technical tradeoffs; influence stakeholders; and lead complex work across teams
• Experience taking ambiguous product or platform requirements from design through implementation, testing, rollout, and production ownership
• Strong programming skills and experience working across frontend, backend, APIs, data stores, and distributed system boundaries
• A demonstrated, genuine AI-first approach to engineering — using AI tools (e.g., Claude Code, Git Hub Copilot, Codex, Cursor) to move faster, build fluency across the stack, and contribute well beyond your core specialty
• 6+ years of experience designing and building production software, including full-stack applications, backend services, developer tools, or internal platforms
• A related technical degree is required
• Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready
• Experience building developer tools, AI coding tool integrations, internal platforms, telemetry systems, or enterprise desktop applications
• Familiarity with React, Type Script, Go, service APIs, event pipelines, analytics systems, or cloud and Kubernetes-based services
• Experience building self-service experiences, dashboards, plugin systems, command-line tools, or standard integration patterns for engineering teams
• Interest in AI developer productivity and helping engineering teams adopt AI tools in ways that are measurable, trustworthy, and scalable