Senior GTM Systems AI and Automation Engineer

Camunda is the enterprise platform for agentic orchestration, enabling organizations to coordinate AI agents, people, and systems across complex, end-to-end business processes. With built-in governance, auditability, and human oversight, Camunda gives enterprises the control they need to move AI from pilots to production — safely and at scale. Trusted by over 700 organizations worldwide, including 9 of top 10 US banks, Camunda helps enterprises boost operational efficiency, accelerate time-to-value, and deliver better customer experiences. Fully remote and global, we are in the middle of something bigger: transforming into an AI-first organisation, built on our own platform. We use Agentic AI to automate, orchestrate intelligent processes, and elevate human contribution across every team. Named GP Bullhound's Top 100 Next Unicorn list, 2025 Great Place to Work certified. Visionary in 2025 Gartner® Magic Quadrant™ for Business Orchestration and Automation Technologies. ranked 3rd in Flexa's 2026 Most Flexible Companies, We're growing fast and looking for top talent to join our team. If you want meaningful work, visible impact and put something genuinely rare on your CV, keep reading.About the Role:Camunda's Revenue Operations organization is looking for a Senior GTM Systems AI and Automation Engineer to design, build and operate the AI-powered infrastructure that connects our go-to-market systems and removes manual work across Sales, Customer Success, Marketing, Partnerships and Account Development. You will join the GTM Systems team – a small group of builders who own a Salesforce-centric revenue stack – and take ownership of its AI and automation layer: agents, LLM integrations, MCP servers, retrieval pipelines, backend services and workflow orchestration. You will partner with GTM leaders to find high-impact problems, scope them, and ship reliable, well-governed solutions iteratively. This is a fully remote role and can be based anywhere we are eligible to hire.What You Will Do: • Design, build and operate AI agents, LLM integrations and automations that connect Salesforce, Gainsight, Slack, Salesloft, Clari, HubSpot, Impartner and the rest of the GTM stack – reducing manual work across Sales, CS, Marketing, Partners and ADR teams. • Own the architecture of the GTM Systems AI layer: MCP servers, APIs, retrieval and context pipelines, reusable agent tools and skills, and serverless or containerized services on Google Cloud Platform (BigQuery, Cloud Run, Cloud Functions). • Ship production-grade LLM capabilities – prompt engineering, RAG, function calling, structured outputs, automated evaluations – with the guardrails to match: validation, fallback logic, confidence thresholds, human escalation paths, access controls, audit logging, and cost and latency management. • Partner with Revenue Operations, Sales, Customer Success, Marketing, Partnerships and SDR/ADR leaders to identify and prioritize automation opportunities, translate ambiguous requirements into maintainable solutions, and deliver incrementally with clear documentation. • Raise the engineering bar for the GTM Systems team: code review, automated testing, CI/CD, security governance, observability and technical documentation; mentor teammates on responsible AI-assisted development. • Design and deploy workflows on orchestration platforms such as Camunda and Clay, and create playbooks and enablement so GTM teams can use and operate automations independently.What You Will Bring to the Role:Must Haves: • 5+ years of software engineering experience (backend development, systems integration, data or analytics engineering, or automation), including at least 2 years shipping LLM or AI capabilities into production business workflows or internal tools. • Strong proficiency in Python and JavaScript/TypeScript (Node.js), with mature Git-based development habits: code review, automated testing, CI/CD. • Hands-on command of LLM patterns – prompt engineering, RAG, function/tool calling, structured outputs, model evaluation – and of their failure modes and mitigations (validation, fallback logic, confidence thresholds, human review, cost and latency control). • Experience integrating with Salesforce (REST/Bulk/Streaming APIs, data model, platform limits; Apex or Flow a plus) and other business systems via APIs and event-driven patterns, and with a cloud platform (GCP preferred: BigQuery, Cloud Run, Cloud Functions, IAM). • Ability to own a problem end-to-end with minimal guidance – scope, design, deliver, operate – and to communicate clearly with engineering and business stakeholders in a remote, asynchronous environment.Nice to Haves: • Experience with the Model Context Protocol (MCP) or similar standards for connecting AI systems to tools and data; agent frameworks; vector databases or retrieval pipelines (pgvector, Pinecone, Weaviate, ChromaDB). • Exposure to AI observability and evaluation tooling (LangSmith, Weights & Biases, or custom eval frameworks). •