Job Overview

Salesforce is hiring for a senior-level Software Engineering LMTS opportunity focused on backend distributed systems. The role is designed for an experienced software engineer who can work on large-scale architecture, production-grade services, scalable SaaS platforms, and modern AI-enabled engineering workflows.

You will work in an engineering environment where software quality, platform stability, scalability, and customer impact are important priorities. The position combines hands-on development with architectural decision-making, technical leadership, mentoring, and the design of systems that can support complex workloads in a multi-tenant cloud environment.

A major focus of this role is applying AI effectively within software development and product workflows. The successful candidate will help design systems where AI agents can work alongside people, while also evaluating AI-generated code for correctness, security, quality, and performance. This makes the opportunity relevant to senior engineers who want to combine distributed systems expertise with emerging AI engineering practices.

Key Responsibilities

• Design and deliver reliable, production-ready backend software using modern engineering practices.
• Apply AI development tools as part of the engineering workflow while maintaining strong standards for security, correctness, optimization, and maintainability.
• Design scalable systems in which AI agents can integrate with human workflows and support efficient business processes.
• Make architecture and system design decisions with attention to performance, scalability, reliability, and future extensibility.
• Contribute across the software development lifecycle, including architecture, implementation, code review, automation, testing, and production delivery.
• Build efficient components and algorithms within a microservices-based, multi-tenant SaaS cloud environment.
• Help maintain shared system context containing architectural decisions, constraints, standards, and technical knowledge that can support reliable AI-assisted engineering.
• Review both human-written and AI-generated code for quality, security, performance, and functional correctness.
• Mentor engineers, provide technical guidance, and help establish strong engineering practices across the team.

Required Skills

The role requires strong foundations in software engineering, object-oriented design, distributed systems, and scalable architecture. Candidates should have substantial experience designing and developing systems that operate at large scale.

Strong programming experience in at least one suitable language is required. Relevant technologies named in the JD include Java, Python, Scala, C#, Go, Node.js, and C++.

Experience developing SaaS applications on a major public cloud platform is expected. Candidates should be comfortable working with AWS, Azure, or Google Cloud Platform and understand the practical considerations involved in building scalable cloud services.

Database knowledge is also important. The role requires familiarity with both relational and non-relational data systems, along with solid SQL skills. Experience with technologies such as PostgreSQL, Trino, Redshift, and MongoDB is relevant.

A strong understanding of distributed systems is essential. Candidates should be comfortable with queues, locking, scheduling, event-driven architecture, workload distribution, and other patterns used to build resilient and scalable services.

Preferred Skills

Experience with microservices, multi-tenant SaaS platforms, cloud-native architectures, and large-scale backend systems will be particularly valuable. Candidates who have worked with AI-assisted development tools, AI agents, or systems that connect AI capabilities with human workflows may have an advantage.

Strong technical leadership experience is important for this level. Examples of architecture ownership, mentoring, code reviews, technical decision-making, and improving engineering standards can demonstrate readiness for the position.

Education

The provided JD does not specify a mandatory educational qualification. The primary requirements are extensive professional software development experience, strong system design knowledge, distributed systems expertise, and demonstrated technical leadership.

Experience

Candidates should have 10 or more years of software development experience, including experience with large-scale system design. This is a senior technical opportunity requiring the ability to work independently on complex architecture and engineering problems while influencing the technical direction of a team.

Required Technologies

• Java
• Python
• Scala
• C#
• Go
• Node.js
• C++
• AWS
• Azure
• Google Cloud Platform
• PostgreSQL
• Trino
• Redshift
• MongoDB
• SQL
• Microservices
• SaaS
• Distributed Systems
• Queues
• Locking
• Scheduling
• Event-Driven Architecture
• Workload Distribution
• AI Development Tools
• AI Agents

Soft Skills

Technical judgment, communication, ownership, and mentoring are important for success in this role. You should be able to explain complex architectural decisions clearly and collaborate effectively with engineers and other stakeholders.

The position also requires critical thinking when reviewing software, especially when AI-assisted tools are involved. Senior engineers should be able to distinguish between code that simply works and code that is secure, maintainable, efficient, scalable, and appropriate for a production environment.

Mentoring is another important aspect of the position. You will be expected to guide engineers, share technical knowledge, participate in code reviews, and contribute to a culture where high engineering standards are consistently maintained.

Benefits of Working in this Role

The JD describes a comprehensive benefits package that includes well-being reimbursement, parental leave, adoption assistance, fertility benefits, and other benefits. Salesforce also provides access to enablement and on-demand training through Trailhead, exposure to executive thought leaders, leadership coaching, and opportunities to participate in community volunteering through its 1:1:1 model.

The technical scope of the role also provides exposure to distributed systems, cloud platforms, SaaS architecture, microservices, databases, AI-assisted engineering, and large-scale system design.

Work Mode

The job description states that Salesforce embraces a hybrid work model.

Location

The position is available in Bangalore, Karnataka, India, and Hyderabad, Telangana, India.

Who Should Apply

This opportunity is suited to experienced backend engineers, distributed systems engineers, software architects, technical leads, and senior software developers with 10 or more years of professional experience.

It is particularly relevant for candidates who have designed large-scale cloud applications and have practical expertise in distributed systems, microservices, databases, public cloud platforms, and scalable architecture. Engineers with strong programming experience in Java, Python, Scala, C#, Go, Node.js, or C++ should consider the role if their background aligns with the system design requirements.

Career Growth

This role provides an opportunity to deepen technical leadership while working on large-scale SaaS and distributed systems. Engineers can broaden their expertise in cloud architecture, multi-tenant platforms, AI-enabled engineering, scalable backend services, and distributed computing.

The mentoring and architectural responsibilities can also strengthen leadership capabilities. Exposure to AI development workflows and agent-based system design provides an opportunity to build skills in an emerging area while applying established software engineering principles.

Application Advice

When applying, emphasize projects where you designed or delivered large-scale distributed systems. Clearly describe the architecture, technologies used, scale of the system, and measurable outcomes such as improved reliability, performance, availability, or cost efficiency.

Highlight hands-on experience with public cloud platforms, microservices, databases, SQL, event-driven systems, queues, scheduling, workload distribution, and scalable SaaS applications. Include examples of technical leadership, architecture ownership, mentoring, and code review responsibilities.

If you have used AI coding assistants, built AI agents, integrated AI into engineering workflows, or evaluated AI-generated code for security and performance, include those experiences with concrete examples.