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# Software Engineering LMTS - Backend Distributed Systems

- **Company:** Salesforce Inc.
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), C++ (Programming Language), Software as a Service, Code Review, Distributed Systems, Python (Programming Language), PostgreSQL, MongoDB, Node.Js, Object-Oriented Software Development, Systems Development Life Cycle, Standard Sql, Scala (Programming Language), Software Engineering, Systems Architecture, Software Organization, Event Driven Architecture, Non-relational Database, Golang, Microservices
- **Published:** September 26, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/28056978/Software-Engineering-Lmts-Backend-Distributed-Systems-Any-Bangalore-7447

## About the Role

* 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

## Description

* 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
 * Design and orchestrate complex, scalable systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale
 * 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


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