About the Role:

Salesforce has immediate opportunities for software engineers who want their lines of code to have significant and measurable positive impact for users, the company's bottom line, and the industry. You will be working with a group of world-class engineers to build the breakthrough features our customers will love, adopt, and use while keeping our trusted CRM platform stable and scalable.

As a Principal Member of Technical Staff (PMTS) at Salesforce, you will leverage deep expertise to lead the architectural design and technical implementation of critical, large-scale systems, ensuring they remain robust, efficient, and innovative.
The software engineer role at Salesforce encompasses architecture, design, implementation, and testing to ensure we build products right and release them with high quality. We embrace the hybrid model and celebrate the individual strengths of each team member while encouraging everyone to grow into the best version of themselves.

Your Impact:

• Build and ship high-quality, production-grade backend software using modern engineering practices, with AI as a core part of your development workflow — pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.

• Design and orchestrate complex distributed systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.

• Contribute to building and maintaining the shared system context — an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.

• Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.

• Lead the end-to-end architecture, technical implementation, and scaling of critical backend and distributed systems, including the design and evolution of highly scalable APIs.

• Drive technical excellence and innovation across the organization by establishing high standards for code quality, performance, reliability, and security; championing best practices, advanced CI/CD pipelines, and emerging enterprise technologies.

• Mentor and inspire team members, fostering a culture of continuous learning and growth, while collaborating with cross-functional teams to align technical strategy with business outcomes.

• Identify and resolve systemic issues — performance bottlenecks, reliability gaps, and technical debt — with long-term, scalable solutions.

Required Qualifications:

• 10+ years of experience in backend software development and large-scale system architecture.

• A demonstrated, genuine AI-first approach to engineering. Using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.

• Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows

• 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.

• Mastery of multiple programming languages and design patterns (e.g., Java, Python, Go, Node.js, Scala) and proven expertise designing distributed systems, microservices, and cloud-native architectures at scale.

• Solid knowledge of web API standards (REST, SOAP, HTTP, JSON) and relational/non-relational databases (e.g., MySQL, PostgreSQL, MongoDB).

• Experience leading technical initiatives, driving cross-team alignment, and influencing engineering direction.

• Strong communication skills — able to write clear design docs and build consensus across teams.

• Degree or equivalent relevant experience required. Experience will be evaluated based on the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.)

Preferred Qualifications:

• Hands-on experience developing SaaS applications over public cloud infrastructure (AWS, Azure, or GCP).

• Proficiency in container orchestration systems (Kubernetes, EKS, Docker).

• Knowledge of microservices architecture and distributed systems design patterns.

• Experience with event-driven architectures, message queues (e.g., Kafka), caching layers (e.g., Redis, Memcached), or data streaming technologies.

• Background in observability, performance engineering, or reliability/site reliability engineering.

• Active participation in open-source communities or contributions to relevant projects.