Lead Software Engineer

Salesforce Data Security is seeking a Lead Software Engineer to architect, build, and scale our unified certificate Registration Authority (RA), the front door for cryptographic trust across our global multi-cloud platform.

This foundational trust layer authenticates and authorizes millions of certificate issuance requests daily, securing machine-to-machine communication, workload identity, and data-in-transit for the world's most trusted enterprise cloud.

You will lead the technical design and delivery of a highly concurrent, multi-substrate Go codebase, stay deep in the code while mentoring senior engineers, and drive architectural consensus across a distributed system where availability and security are non-negotiable.

This is an AI-first engineering team: you use advanced AI coding assistants, prompt engineering, and shared-system-context tools daily to accelerate your workflows, review code, and generate comprehensive tests, setting the standard for AI-augmented software development.

Responsibilities

• Architect, build, and maintain the unified Registration Authority (RA) that serves as the single certificate-issuance front door for a global, multi-cloud platform.
• Design and optimize highly concurrent, multi-substrate build paths in Go, ensuring seamless deployment across diverse public-cloud environments.
• Develop and scale both synchronous and asynchronous certificate issuance paths using robust distributed state-machine orchestration.
• Implement strictly evaluated hierarchical policy engines and authorization controls to validate substrate-specific workload identity and attestation.
• Drive robust certificate lifecycle management and automation by integrating with and abstracting multiple public and private Certificate Authorities (CAs).
• Lead the team's engineering excellence by writing resilient, observable, and strictly tested code capable of surviving underlying infrastructure degradation.
• Instrument comprehensive telemetry, distributed tracing, and alerting to maintain stringent availability and performance service level agreements (SLAs).
• Act as a technical multiplier, mentoring engineers, conducting rigorous code reviews, and raising the bar for distributed systems design.
• Partner with Security Architecture to translate complex compliance requirements into automated, scalable software controls.
• Respond to and resolve complex distributed systems escalations, identifying root causes and deploying durable architectural fixes.
• Elevate team productivity by establishing best practices for AI-augmented software development and prompt engineering.
• Build and ship high-quality, production-grade 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 systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
• Contribute to building and maintaining shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably, and critically evaluate code (human- or AI-generated) for correctness, quality, security, and performance.

Requirements

• 9+ years of professional software development experience, with a proven track record of designing and operating large-scale distributed systems.
• Deep, production-grade expertise in Go (Golang), Java, or Rust, including advanced concurrency patterns, memory management, and multi-substrate build configurations.
• Extensive experience deploying and operating highly available, mission-critical services across public cloud providers such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).
• Ability to design resilient Representational State Transfer (RESTful) and gRPC web services, backed by robust distributed state machines and asynchronous processing pipelines.
• Strong background in observability (telemetry, distributed tracing, metrics) and modern continuous integration/continuous delivery (CI/CD) deployment pipelines.
• Proficiency with AI coding assistants and shared-context workflows that enhance engineering velocity.
• 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.
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Benefits

• Time off programs
• Medical, dental, vision
• Mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program

Salary

• The typical base salary range for this position is $172,500 - $260,100 annually.
• In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.