Description
Sales Cloud AI is revolutionizing how organizations strategize, execute, and refine their lead outreach and pipeline management. We are looking for engineers to develop the Sales Intelligence Platform (SIP) within Sales Cloud. In this role, you will be responsible for the architecture, development, and operation of a high-scale, low-latency platform that manages real-time ingestion and streaming pipelines.
The Sales Intelligence Platform (SIP) processes conversational data from voice, video, and email to power various Sales Cloud AI agents. These agents provide tools for lead outreach and pipeline management, significantly boosting sales productivity. By generating intelligent insights from conversational data, the platform empowers sellers to enhance their overall efficiency.
Required skills and experience
Degree in Computer Science (B.S. required, M.S. preferred) with a solid grasp of object-oriented design and principles.
Over 7+ years of practical experience architecting, implementing, and managing durable distributed systems at scale for major enterprise cloud providers.
Proven track record in constructing high-availability, large-scale distributed architectures for client-facing environments.
Extensive knowledge of contemporary public cloud frameworks (including AWS, GCP, or Azure) and high-performance backend infrastructure.
Proficiency in object-oriented programming with mastery in at least one language such as Java, Go, Python, C++, or Ruby.
Familiarity with infrastructure automation, cloud provisioning, and AI-assisted development methodologies.
Strong interpersonal and professional communication skills, with a focus on cross-functional collaboration and leadership.
Commitment to technical excellence through meticulous attention to detail and proactive mentorship of junior engineers.
Preferred qualification
Proven ability to develop low-latency, large-scale data ingestion pipelines
Background in creating enterprise-grade, AI-driven sales solutions
History of architecting distributed real-time streaming systems
Expertise with message queuing technologies like Kafka
Hands-on experience with open-source ecosystems including Flink, Spark, Storm, Cassandra, Zookeeper, and MongoDB
At least 3 years of experience with Java, Spring, microservices, REST APIs, and distributed systems
Knowledge of deployment architectures and CI/CD tools such as Jenkins, Terraform, and Spinnaker
Familiarity with container orchestration platforms like Docker, Kubernetes, Helios, Fleet, or Mesos
Experience managing and monitoring mission-critical infrastructure, including logging, alerting, and reporting services
Proficiency in using NoSQL and SQL databases such as PostgreSQL and MongoDB
Deep understanding of high-volume distributed databases, data pipelines, and large-scale systems
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.