Senior Software Engineer, Internally Deployed Products

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. The Mission The Foundry is ClickUp's internal AI innovation lab — embedded inside GTM Systems and accountable for turning AI capabilities into production-grade, internally deployed products that make every GTM function faster and smarter. We build the infrastructure that powers AI-first work across Sales, Marketing, Post-Sales, and Revenue Operations.

As the Senior Software Engineer on this team you will own the technical delivery of our MCP server platform, agent orchestration layer, and internal tooling — shipping production systems used daily by hundreds of ClickUp employees, and scaling your own throughput by treating AI tools as first-class engineering collaborators. What You'll Own MCP Server Platform Design, build, and operate Model Context Protocol servers that expose CRM, ticketing, analytics, and communication data to AI agents across the GTM stack Implement Okta PKCE authentication flows and RBAC policy enforcement so agents access only the data they're authorized to touch Maintain deployment infrastructure on AWS (Bedrock, Lambda, ECS, API Gateway) and contribute to GCP workloads where applicable Own observability: structured logging, distributed tracing, latency SLOs, and on-call runbooks for every production server Agent Orchestration & AI-Native Products Build and maintain multi-step autonomous agents that execute end-to-end GTM workflows — lead qualification, deal room assembly, onboarding automation, support triage, and more Architect prompt engineering frameworks, tool-call schemas, and agent evaluation harnesses that make AI behavior predictable and auditable Integrate with LLM providers (Anthropic, OpenAI, AWS Bedrock AgentCore) and maintain version-pinned, cost-tracked model configurations Deliver AI-powered internal applications (web apps, CLI tools, Slack integrations) that non-technical GTM stakeholders use without friction GTM Platform Engineering Own full-stack feature delivery across TypeScript/Node.js backends and React/TypeScript frontends for internal tooling Write Python automation scripts, ETL pipelines, and data transformation layers that feed GTM analytics and AI context Collaborate with Systems Engineering and GTM Engineering teams on cross-cutting API standards, data contracts, and integration patterns Conduct code reviews, establish engineering standards, and actively mentor junior engineers toward higher leverage AI-Native Development Practice Use AI coding assistants (Claude, Cursor, GitHub Copilot) as primary engineering accelerators — not supplements — to ship at a pace that punches above a single engineer's weight Document AI usage patterns, prompt templates, and agentic workflows so the team's collective throughput compounds Stay current on MCP protocol evolution, agent frameworks (LangGraph, CrewAI, custom), and emerging LLM capabilities; bring back what matters Required Qualifications 5+ years of professional software engineering experience with production systems Expert-level TypeScript and Node.js — idiomatic, typed, testable server-side code Strong Python — automation scripts, data pipelines, and scripting for AI/ML tooling Meaningful AWS deployment experience: Lambda, Bedrock, ECS/Fargate, API Gateway, IAM, Secrets Manager, CloudWatch Demonstrated experience integrating with LLM APIs (OpenAI, Anthropic, AWS Bedrock, or equivalent) and shipping AI-powered features to real users Solid foundation in REST API design, OAuth 2.0 / OIDC authentication, and secure credential management Experience with CI/CD pipelines, infrastructure-as-code (Terraform, CDK, or SAM), and cloud cost awareness Clear written communication: design docs, ADRs, and runbooks that others actually read Track record of using AI tools (LLM assistants, copilots, agentic workflows) as a genuine productivity multiplier — not a gimmick Strongly Preferred Hands-on experience with MCP (Model Context Protocol) — building servers, defining tool schemas, or operating multi-server agent environments GCP experience (Cloud Run, BigQuery, Cloud Functions) to complement AWS work Salesforce, HubSpot, or other CRM API integration work — understanding GTM data models is a significant advantage React or Next.js front-end capability to ship internal dashboards and tooling without hand-offs Familiarity with agent orchestration frameworks: LangGraph, AutoGen, CrewAI, or custom orchestration patterns Experience in a GTM Systems, RevOps, or Sales Engineering context Okta / identity provider integration work (PKCE flows, SCIM, token management) How We Operate The Foundry runs on three principles that every team member is expected to embody: Ownership — You own the full lifecycle of what you build: design, delivery, observability, and iteration.