Software Engineering LMTS at Salesforce

Job description

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. The Data Security Fabric team is seeking a Lead Data Engineer to help architect and build a secure, cloud-native, and highly scalable Data Platform designed to measure, mitigate, and reduce enterprise risk. By unifying disparate security data across the organization, our platform will provide actionable insights to proactively identify risks and automate remediation efforts. As a Lead Engineer on our team, you will be responsible for designing and implementing a robust data platform that collects and processes critical security signals from a wide range of sources. These include comprehensive asset information (hardware and software) across Salesforce, vulnerability data from large-scale scanning tools such as Tenable and Prisma, user identity and access data, security signals from 10+ Salesforce platforms (e.g., Core, Hyperforce, Data Cloud, Slack, Tableau, Heroku, MuleSoft), and other security signals from over 15 different environments like AWS, GCP, CRM systems, and third-party vendor platforms. You will use leading-edge technologies to build the next-generation security data platform, creating a vendor-agnostic core security system. AI and machine learning are first-class capabilities of this platform — you will help design LLM- and ML-driven workflows for security signal enrichment, anomaly detection, risk scoring, and automated triage, and integrate agentic patterns (RAG, tool-use, evals) into the platform's remediation and investigation flows. You will also help establish data governance and quality frameworks that support risk management, regulatory compliance, and continuous security improvement across the enterprise. This is an exciting opportunity for experienced engineers with a passion for distributed systems, big data processing, AI/ML, and security. You will play a key role in shaping the future of security at Salesforce, helping ensure the platform's scalability, reliability, and alignment with industry best practices. Your work will have a direct impact on Salesforce's security strategy — driving innovation, improving risk management, using AI to accelerate detection and response, and enabling automation of security remediation across the organization. If you're an engineer looking to grow your technical expertise in cloud-native systems, cybersecurity, big data processing, and applied AI, this role offers strong opportunities for professional development, along with meaningful visibility and business impact. Responsibilities Learn and adapt to Salesforce's security strategies, goals, objectives, and capabilities to help improve security posture. Lead the design and architecture of a highly scalable and secure data platform that ingests and processes diverse security data sources across 10+ Salesforce platforms and 15+ external environments. Build and optimize data pipelines to collect, store, and analyze security signals from tools and platforms (e.g., vulnerability scanners, asset management systems, identity and access control systems) running across multiple environments (AWS, GCP, Salesforce, CRM, vendor systems, etc.). Design and integrate AI/ML and LLM-driven capabilities into the platform — in