Software Engineering LMTS - Backend Distributed Systems
Salesforce, India - Bangalore +1
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Overview
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Job Category Software Engineering
Job Details
Nice to have
- Hands-on experience using AI-assisted development tools in your daily engineering workflow
- Experience designing systems where AI agents work alongside human workflows
- Experience with multi-tenant, microservices-based SaaS architectures
- Track record of mentoring engineers and providing technical guidance
What You’ll Actually Be Doing
- Strong proficiency in system design, programming languages, and platforms
- Deep knowledge of designing distributed file systems in both on-premises and cloud environments.
- Strong knowledge of object-oriented programming and scripting languages, including Java and Python.
- Strong SQL skills and experience with relational and non-relational databases (e.g., PostgreSQL, Trino).
- Experience developing SaaS products on public cloud infrastructure (AWS, Azure, GCP).
- Proven experience in designing and developing distributed systems at scale.
- Proficiency in queues, locks, scheduling, event-driven architecture, and workload distribution.
- Deep understanding of relational and non-relational databases.
- Strong understanding of software development best practices and demonstrated leadership skills.
- 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