GTM DevOps Engineer

At ClickUp , we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. Job Summary We are looking for a GTM DevOps Engineer to join our Business Systems team and own the reliability, automation, and delivery infrastructure behind our Go-To-Market (GTM) technology stack. This role sits at the intersection of platform reliability and CI/CD engineering, ensuring that our critical business systems — including Salesforce, NetSuite, MuleSoft, Workato, and an expanding portfolio of AI-powered workloads — are deployed consistently, operate resiliently, and scale with the business. You will partner closely with Business Systems developers, architects, and business stakeholders to build and maintain the pipelines, monitoring frameworks, and operational standards that keep our GTM systems healthy and our release cycles fast and predictable. As our team builds and deploys AI agents across GCP Cloud Run and AWS Bedrock AgentCore, you will serve as the infrastructure and deployment owner for these workloads — bringing engineering discipline to an environment where AI-generated code is increasingly entering production. This is a hands-on engineering role for someone who thrives in complexity, takes ownership of platform uptime, and brings a software engineering mindset to business application operations — directly supporting GTMSOE's broader mission of operational excellence across the GTM org. Key Responsibilities CI/CD & Release Engineering • Design, build, and maintain CI/CD pipelines for Salesforce (SFDX/Salesforce CLI), NetSuite (SuiteScript/SuiteBundler), MuleSoft (Anypoint Platform), and Workato; establish branching strategies, environment promotion standards, and release gating processes across all GTM platforms. • Extend CI/CD practices to cover AI agent workloads deployed on GCP Cloud Run and AWS Bedrock AgentCore — including containerized builds, deployment pipelines, and automated validation gates. • Implement safe rollout patterns — including feature toggles, phased launches, automated validation, smoke tests, and rollback procedures — to reduce deployment risk on business-critical changes. Platform Reliability & Observability • Own SLA/SLO definitions for core GTM systems; standardize monitoring, alerting, and runbook patterns across quote-to-cash and GTM integrations, with proactive health checks and synthetic monitoring for critical flows (e.g., Salesforce ↔ NetSuite, Workato). • Extend observability coverage to GCP Cloud Run workloads — Cloud Scheduler jobs, agent pipelines, and integration microservices — and AWS-hosted agent infrastructure. • Conduct root cause analysis (RCA) for platform incidents and drive post-incident reviews with actionable remediation plans. Cloud Infrastructure & Environment Management • Manage sandbox, staging, and production environment lifecycles across GTM platforms — including refresh cycles, data masking, environment segmentation, and promotion standards that balance speed with reliability. • Own cloud infrastructure for Business Systems-operated workloads on GCP (Cloud Run, Cloud Scheduler, Cloud Secret Manager, GCS, Artifact Registry) and AWS (Lambda, S3, EventBridge, Secrets Manager, Bedrock AgentCore); apply IaC practices to make provisioning repeatable and auditable. • Establish base image pinning, dependency vulnerability scanning, and supply chain security practices for containerized workloads — particularly AI-generated codebases deployed via tools like Cursor or Claude Code. • De