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 the top 10 US banks, Camunda helps enterprises boost operational efficiency, accelerate time-to-value, and deliver better customer experiences.

Fully remote and global, Camunda is transforming into an AI-first organization, built on its own platform. They use Agentic AI to automate, orchestrate intelligent processes, and elevate human contribution across every team.

Named GP Bullhound’s Top 100 Next Unicorn list in 2025, 2025 Great Place to Work certified, and ranked as a Visionary in the 2025 Gartner® Magic Quadrant™ for Business Orchestration and Automation Technologies. They are also ranked 3rd in Flexa's 2026 Most Flexible Companies.

About the Role:

Camunda's Revenue Operations organization is seeking a Senior GTM Systems AI and Automation Engineer to design, build, and operate the AI-powered infrastructure connecting their go-to-market systems and removing manual work across Sales, Customer Success, Marketing, Partnerships, and Account Development. This fully remote role can be based anywhere they are eligible to hire.

What You Will Do:

• Design, build, and operate AI agents, LLM integrations, and automations connecting Salesforce, Gainsight, Slack, Salesloft, Clari, HubSpot, Impartner, and other GTM stack tools, reducing manual work across Sales, Customer Success, Marketing, Partners, and Account Development and Revenue teams.

• Own the architecture of the GTM Systems AI layer, including 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 such as prompt engineering, RAG, function calling, structured outputs, automated evaluations, with guardrails like 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 through 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 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 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).

• Familiarity with orchestration platforms such as Camunda or Clay, and prior work in Revenue Operations, GTM Systems, Sales Operations, or Marketing Operations in B2B SaaS.

• Building lightweight interfaces for AI tools (React, Slack Block Kit, dashboards); Salesforce certifications (Platform Developer I/II, Integration Architect).