Our Security Software Engineering team builds and operates highly scalable, fault-tolerant, distributed systems to deliver cloud-scale security software services. We provide the fundamental building blocks to improve and preserve customer trust in Salesforce’s products across multiple public cloud substrates and our own network infrastructure. We architect and implement our services, to protect Salesforce products/infrastructure and defend against malicious attacks. . You will have the unique opportunity to learn from the best industry security experts and integrate that into your software and service engineering.
Built-in Trust. Hyperforce’s security architecture continuously verifies and limits users to appropriate levels of access to customer data (*this is what our IAM team does*), protecting exposure of sensitive information due to human error or misconfiguration (*this is Data Protection, i.e. PKI, Secrets management, etc.*). Encryption, at rest and in transit, comes standard, ensuring the privacy and the security of data from Salesforce and public cloud providers (*SDS creates these capabilities in a PaaS model, so other Salesforce teams can call these services and make sure their environments adhere to these security requirements*).
Experience building large-scale distributed systems, especially in cloud environments
Deep understanding of object-oriented programming and experience with at least one object-oriented programming language (Java, Go, Python C++, C#)
Experience with public cloud services (AWS or Google Cloud Platform or Azure)
Experience with Scrum or other agile development methodologies, with attention to code quality, delivering secure code
Experience working in a complex team environment. Able to deliver under pressure.
Good knowledge of operating systems (Linux, Mac and Windows)
A related technical degree required
Prior security knowledge is not required.
Knowledge of working with relational databases MySQL, Postgres
Familiar with open source technologies, such as ZooKeeper, MongoDB
Experience with big data and pipeline technologies, such as Hadoop, Kafka
Knowledge or experience with machine learning
Experience building services with Docker and Kubernetes
Good knowledge with network technologies, such as TCP/IP, DNS or load balancer