Senior GTM Systems AI and Automation Engineer
Camunda · Remote
About this role
**Senior GTM Systems AI and Automation Engineer (Fully Remote)** Camunda is the enterprise platform for agentic orchestration—coordinating AI agents, people, and systems across complex, end-to-end business processes with governance, auditability, and human oversight. Camunda is growing fast and is transforming into an **AI-first organisation**, built on its own platform. This role sits in Revenue Operations and will help connect and automate the go-to-market stack across Sales, Customer Success, Marketing, Partnerships, and ADR. --- ### About the Role Join the **GTM Systems** team (Salesforce-centric revenue stack) and take ownership of its **AI and automation layer**—including agents, LLM integrations, MCP servers, retrieval pipelines, backend services, and workflow orchestration. You’ll partner with GTM leaders to identify high-impact problems, scope them, and ship **reliable, well-governed** solutions iteratively. --- ### What You Will Do - **Design, build, and operate** AI agents, LLM integrations, and automations connecting Salesforce, Gainsight, Slack, Salesloft, Clari, HubSpot, Impartner, and more—reducing manual work across GTM teams. - Own the architecture of the **GTM Systems AI layer**: MCP servers, APIs, retrieval/context pipelines, reusable agent tools/skills, and serverless/containerized services on **GCP** (BigQuery, Cloud Run, Cloud Functions). - Ship **production-grade LLM capabilities** (prompt engineering, RAG, function calling, structured outputs, automated evaluations) with guardrails such as validation, fallback logic, confidence thresholds, human escalation, access controls, audit logging, and cost/latency management. - Work with Revenue Operations and GTM leaders to identify/prioritize automation opportunities, translate requirements into maintainable solutions, and deliver incrementally with clear documentation. - Raise the engineering bar: code review, automated testing, CI/CD, security governance, observability, technical documentation, and mentor teammates on responsible AI-assisted development. - Design and deploy workflows on orchestration platforms such as **Camunda** and **Clay**, and create playbooks so GTM teams can operate automations independently. --- ### What You Will Bring to the Role **Must Haves** - **5+ years** software engineering experience; **2+ years** shipping LLM/AI capabilities into production business workflows or internal tools. - Strong proficiency in **Python** and **JavaScript/TypeScript (Node.js)**; mature Git habits (code review, automated testing, CI/CD). - Hands-on command of LLM patterns (prompt engineering, RAG, function/tool calling, structured outputs, model evaluation) and failure-mode mitigations (validation, fallback, confidence thresholds, human review, cost/latency control). - Experience integrating with **Salesforce** (REST/Bulk/Streaming APIs, data model, platform limits; Apex or Flow a plus) and other systems via APIs/event-driven patterns; cloud experience (**GCP preferred**: BigQuery, Cloud Run, Cloud Functions, IAM). - Ability to own problems end-to-end (scope → design → deliver → operate) and communicate clearly in a remote, asynchronous environment. **Nice to Haves** - Experience with **Model Context Protocol (MCP)** or similar standards; agent frameworks; vector DBs/retrieval pipelines (pgvector, Pinecone, Weaviate, ChromaDB). - Exposure to AI observability/evaluation tooling (LangSmith, Weights & Biases, or custom eval frameworks). - Familiarity with
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