Software Engineering SMTS

Role details

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Role Description We are looking for a Software Engineer, Senior Member of Technical Staff (SMTS), to design, build, automate, and operate reliable, secure, and scalable cloud infrastructure and production platforms. You will work with software engineers, infrastructure teams, security partners, and product teams. Your work will improve service availability, deployment reliability, operational efficiency, and developer productivity. The ideal candidate has strong experience with software development, public cloud and cloud-native technologies, infrastructure automation, CI/CD, observability, and production operations. They also take a practical, AI-first approach to their work. This is an engineering-focused development role. We expect automation and software development to replace repetitive manual operations. You approach ambiguous infrastructure and production problems methodically. You understand system behavior across application and infrastructure layers. You use modern engineering practices, including AI-assisted development, to improve reliability, automation, and delivery effectiveness. Required Qualifications 6+ years of experience designing and building production software. This includes full-stack applications, backend services, developer tools, or internal platforms. Strong programming skills and experience working across frontend, backend, APIs, data stores, and distributed system boundaries. Experience designing, deploying, or operating production workloads on public cloud platforms such as AWS, Azure, or Google Cloud Platform. Development or automation experience using Core Java, Python, Go, or another programming language. You can build maintainable, production-quality automation, tools, services, or APIs. Strong understanding of cloud infrastructure concepts, including compute, storage, networking, load balancing, identity and access management, security, high availability, and disaster recovery. Experience with containerization and cloud-native technologies such as Docker, Kubernetes, or comparable container orchestration platforms. A demonstrated AI-first approach to engineering. You use AI tools (for example, Claude Code, GitHub Copilot, Codex, or Cursor) to work faster, build fluency across the stack, and contribute beyond your core specialty. Experience with Infrastructure as Code and configuration automation using tools such as Terraform, CloudFormation, Ansible, Helm, or comparable tooling. Experience building, maintaining, or improving CI/CD pipelines and automated build, test, deployment, and release workflows. Familiarity with databases (Postgres, HBase, Oracle, or similar) and database cluster technologies such as Oracle RAC (Real Application Clusters). Experience with Linux systems and working knowledge of operating systems, networking, process, memory, storage, and performance fundamentals. Experience with production observability using logs, metrics, traces, dashboards, and alerting platforms. Understanding of distributed-system and reliability concepts, including scalability, fault tolerance, resiliency, service dependencies, capacity, availability, and performance. Experience troubleshooting complex production issues across application, infrastructure, networking, and cloud layers. Experience working across the software and infrastructure delivery lifecycle: design, implementation, testing, deployment, monitoring, incident response, and continuous improvement. Experience using AI development tools or techniques for automation, software development, troubleshooting, testing, debugging, and documentation. Strong analytical and problem-solving skills, including the ability to diagnose complex infrastructure and production problems systematically. Effective written and verbal communication skills and the ability to collaborate across engineering and operational teams. Preferred Qualifications Experience operating large-scale distributed systems or high-availability production platforms. Experience with Kubernetes ecosystem technologies, service discovery, ingress, service mesh, autoscaling, or container platform engineering. Experience building internal developer platforms, self-service infrastructure, deployment frameworks, or operational automation. Experience developing backend services, APIs, command-line tools, controllers, operators, or automation frameworks. Advanced prompt engineering skills. You can write precise, structured prompts and build the system context that makes AI outputs reliable, secure, and production-ready. Experience with Site Reliability Engineering (SRE) practices, including service level objectives (SLOs), service level indicators (SLIs), error budgets, capacity management, and incident management. Experience with cloud security, IAM, secrets management, vulnerability management, policy enforcement, and infrastructure security controls. Experience with observability technologies such as Prometheus, Grafana, OpenTelemetry, Splunk, or comparable platforms. Experience with databases, caching systems, messaging platforms, or distributed data infrastructure. Familiarity with multi-region, multi-cloud, disaster recovery, or large