Lead Backend Software Engineer

Description

Note: By applying to the Software Backend Development posting, recruiters and hiring managers across the organization hiring Software Engineers will review your resume. Our goal is for you to apply once and have your resume reviewed by multiple hiring teams.

Salesforce has immediate opportunities for software developers 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. 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 pride ourselves on writing high-quality, maintainable code that strengthens the stability of the product and makes our lives easier. We embrace the hybrid model and celebrate the individual strengths of each team member while encouraging everyone on the team to grow into the best version of themselves. We believe that autonomous teams with the freedom to make decisions will empower the individuals, the product, the company, and the customers they serve to thrive.

Your Impact

As a Lead Backend Software Engineer, your responsibilities will include:

• 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, scalable systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
• Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
• Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
• Make architectural and design decisions with a strong focus on performance, scalability, and future extensibility
• Contribute to all phases of the SDLC — including design, implementation, code reviews, automation, and testing — in a hybrid engineering model
• Build efficient components and algorithms within a microservices-based, multi-tenant SaaS cloud environment
• 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.
• Mentor engineers and provide technical guidance to drive high standards across the team
  
  

• 7+ years of software development experience with a track record in large-scale system design.
• Deep knowledge of object-oriented programming and scripting languages: Java, Python, Scala, C#, Go, Node.js, and/or C++.
• Strong SQL skills and hands-on experience with relational and non-relational databases (e.g., PostgreSQL, Trino, Redshift, MongoDB).
• Experience developing SaaS products over public cloud infrastructure (AWS, Azure, or GCP).
• Proven experience designing and developing distributed systems at scale.
• Proficiency in queues, locks, scheduling, event-driven architecture, and workload distribution, along with a deep understanding of relational and non-relational databases.
• Demonstrated technical leadership and a deep understanding of software development best practices.
• 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-assisted development tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) as an integrated part of your engineering workflow/
• Advanced prompt engineering skills: ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
• 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.)
  
  

• Technical expertise in Generative AI, particularly with RAG systems and Agentic workflows that use large language models
• Experience with Big Data, ML pipelines, and S3
• Hands-on experience with streaming technologies like Kafka
• Experience with Elasticsearch
• Experience with Terraform, Kubernetes, and Docker
• Experience working in a high-growth, multinational engineering organization