Software Engineer (MTS), Frontier Strike (EntSecTech)

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About the role

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 Experience Frontier Strike, part of Enterprise Security Technology (EntSecTech), builds and operates the Harness Orchestrator, an autonomous AI red-teaming platform that continuously tests our own identity and AI-integrated systems the way a real attacker would. This role builds the orchestration engine, policy gateways, and secrets-isolation systems that let the team safely point automated adversarial testing at production. AI serves as a core part of the development workflow here, pairing hands-on distributed-systems engineering with modern AI-assisted tooling to ship secure, production-grade code faster. What You'll Actually Be Doing • Design and extend Go microservices that orchestrate multi-container test suites (primary and utility containers, shared ephemeral volumes, lifecycle synchronization) so new attack and test techniques can be onboarded as repeatable, automated suites. • Build policy-based sidecar gateways that mediate every test suite's access to its target system, whether mocked, staging, or production, enforcing least-privilege and blast-radius limits as tests move up the risk tiers. • Implement pipeline stages that dedupe, suppress noise, and auto-escalate critical findings (injection, server-side request forgery (SSRF), privilege escalation, data exfiltration) so only real signal reaches the persistent findings store. • Design per-test-suite secrets isolation (dedicated vault, pod, and service account per suite) with automated credential rotation, so a compromised or misbehaving test suite can't reach another suite's credentials. • Deploy and operate containerized workloads on Kubernetes via Helm and Terraform on Amazon Web Services (AWS), at a scale where individual test runs can cost significantly more or less depending on suite complexity. • Integrate with internal large language model (LLM) gateway services to track token usage and cost per scan, and build throttling and authorization controls for expensive test executions. • Implement role-based access control (RBAC), network sandboxing, and geofencing so automated red-teaming can be safely extended from test environments to production. • Monitor and troubleshoot the platform's distributed components, ensuring findings-pipeline data integrity and proactively catching misconfigurations before they become production incidents. • Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow, pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code. • Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. • Contribute to building and maintaining shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably. Critically evaluate code, whether human-

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