Senior Software Engineer, Internally Deployed Products
Senior Software Engineer building and operating the MCP server platform, autonomous AI agents, and internal GTM tooling at ClickUp's Foundry AI lab. Requires 5+ years experience, expert TypeScript/Node.js and Python, AWS/LLM integration skills, and daily use of AI coding tools to ship production systems used by hundreds of employees.
About the job
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).
Skills
TypeScript, Node.js, Python, AWS, Aws Bedrock, AWS Lambda, Aws Ecs, Aws Api Gateway, LLM APIs, React, Terraform, Oauth 2.0, Mcp, LangGraph, GCP
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