Software Engineering Lmts

Salesforce Salesforce · Enterprise · Bangalore, India, India

Salesforce is seeking an experienced Software Engineer to build and ship production-grade software with AI as a core part of the development workflow. The role involves designing and orchestrating complex, scalable systems where AI agents integrate into human workflows, making architectural decisions, contributing to all phases of the SDLC, and building efficient components within a SaaS cloud environment. The engineer will also contribute to shared system context for AI reliability and critically evaluate code, including AI-generated code.

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 by 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. Make architectural and design decisions with a strong focus on performance, scalability, and future extensibility
  4. Contribute to all phases of the SDLC, including design, implementation, code reviews, automation, and testing in a hybrid engineering model
  5. Build efficient components and algorithms within a microservices-based, multi-tenant SaaS cloud environment

Skills

Required

  • 10+ years of experience in software development and large-scale system design
  • Strong software engineering fundamentals, including object-oriented design, distributed systems, and scalable architecture
  • Proficiency in one or more programming languages such as Java, Python, Scala, C#, Go, Node.js, or C++
  • Experience developing SaaS applications on public cloud platforms (AWS, Azure, or GCP)
  • Strong understanding of relational and non-relational databases (e.g., PostgreSQL, Trino, Redshift, MongoDB) and solid SQL skills
  • Experience with distributed systems concepts such as queues, locking, scheduling, event-driven architecture, and workload distribution
  • Deep understanding of software development best practices, with demonstrated technical leadership

What the JD emphasized

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

Other signals

  • AI agents integrate seamlessly into human workflows
  • AI as a core part of your development workflow
  • 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)