Why This Job is Featured on The SaaS Jobs
This AI GTM Engineer role is notable in SaaS because it formalises the emerging “AI operations” layer inside revenue teams, where LLM-driven systems are treated as production infrastructure rather than ad hoc tooling. Situated within a B2B platform company serving global payroll and payments, the remit reflects how mature SaaS organisations are starting to operationalise AI across demand generation, content, and sales development workflows with governance and observability.
For a SaaS career, the long-term value lies in building cross-functional fluency at the boundary of marketing operations, data integrations, and applied AI. Designing agent orchestration, QA frameworks, and guardrails maps closely to challenges faced across modern SaaS go-to-market stacks: connecting CRMs and automation platforms, standardising data flows, and measuring quality and cost at scale. The experience is portable to other SaaS teams investing in AI-enabled productivity and lifecycle marketing.
The role will suit professionals who prefer building systems that other teams rely on, and who enjoy translating between technical constraints and commercial workflows. It is a strong match for someone comfortable owning end-to-end implementation details, from API integrations to monitoring, while collaborating with stakeholders across marketing, security, and internal AI functions.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Papaya Global is a rapidly growing, award-winning B2B tech unicorn with an ambitious mission to revolutionize the payroll and payments industry. With over $400M raised from multiple tier-one investors, our innovative technology provides a comprehensive solution for managing global workforces, encompassing everything from hiring and onboarding to managing and paying employees in over 160 countries.
We are seeking an AI GTM Engineer to join our Marketing team in Israel. In this foundational role, you will design, build, and govern the AI agent infrastructure that powers Papaya’s marketing engine — giving every team member AI-powered leverage across Growth, Demand Gen, Content, SDRs, and more. You will sit at the intersection of engineering, marketing operations, and AI product thinking, reporting directly to the Marketing Ops Lead.
Responsibilities:
- Design and build the full AI agent stack for the marketing org — personal agents per team member, shared service agents, and orchestration agents that connect them
- Own the technical architecture end-to-end: trigger design, LLM selection, data integrations, output formatting, and approval routing to the right person at the right time
- Build and maintain the prompt library, golden datasets, and QA framework — running structured testing before every agent goes live
- Define and enforce guardrails across all agents: brand voice compliance, hallucination prevention, budget limits, and escalation triggers
- Own the monitoring and observability layer — tracking every agent run for latency, cost, quality score, and error rate
- Design and maintain the data flow architecture connecting marketing systems, AI APIs, and delivery channels
- Train the full marketing team to work with their AI agents and act as the internal expert on AI tools and workflows
- Collaborate with Papaya’s AI team and Security team on architecture standards, data security, and access controls
- Continuously learn and apply emerging trends in AI agent design and LLM tooling, bringing new capabilities to the team proactively
Requirements:
- Solid understanding of B2B SaaS marketing — demand gen, ABX, SDR outreach, and content workflows
- Hands-on experience with at least one LLM API (Anthropic Claude or OpenAI) building real automated workflows, not just demos
- Proven experience with workflow automation tools such as n8n, Zapier, or Make — building multi-step workflows connected to real business systems
- Solid understanding of REST APIs and webhooks — you have built and debugged multi-system integrations
- Experience designing and evaluating prompts to hit measurable quality targets
- Coding knowledge in Python or JavaScript — vibe coding with AI assistance is absolutely fine; deep software engineering experience is not required
- Familiarity with CRM and marketing automation data models (Salesforce, HubSpot)
- Strong communication skills — you translate technical constraints into plain language for non-technical teams daily
