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 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.

• 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

• 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

• 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

• 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

• 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

• 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)

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. We don't have a separate ops hand-off.
• Velocity — We ship to production in days, not quarters. AI tools are how we maintain that pace without sacrificing quality.
• Atomicity — Every deliverable is a discrete, composable unit — an MCP server, an agent, an API. Nothing we build requires everything else to work.

This role is a strong fit if you are genuinely excited to work at the intersection of AI infrastructure and internal product — not just as a user of AI, but as someone building the layer that makes AI useful for an entire go-to-market organization. You are comfortable with ambiguity, you default to shipping, and you see every piece of internal tooling as a product that deserves operational discipline.

This role is not a fit if you need heavily defined requirements before starting work, p