Lead Backend Software Engineer

Salesforce · Enterprise · Tel Aviv, Israel

Lead Backend Software Engineer at Salesforce, focusing on building and shipping production-grade software with AI as a core part of the development workflow. The role involves designing and orchestrating scalable systems where AI agents integrate into human workflows, developing high-quality code for a cloud platform, and contributing to shared system context for AI reliability. Requires strong backend engineering experience, cloud infrastructure knowledge, and advanced prompt engineering skills.

What you'd actually do

  1. 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.
  2. Design and orchestrate complex, scalable systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
  3. Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
  4. Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
  5. Make architectural and design decisions with a strong focus on performance, scalability, and future extensibility

Skills

Required

  • 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.

Nice to have

  • 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

What the JD emphasized

  • 7+ years of software development experience with a track record in large-scale system design.
  • A demonstrated, genuine AI-first approach to engineering.
  • Advanced prompt engineering skills: ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.

Other signals

  • AI agents integrate seamlessly into human workflows
  • AI as a core part of your development workflow
  • Advanced prompt engineering skills
  • Critically evaluate code (human or AI-generated)