This is a hybrid Builder-Seller role in our newly formed AI Natives unit. As an AI GTM Engineer, you won't just execute a playbook — you'll code it. You'll sit at the intersection of Sales, Data Science, and Engineering to build automated, agentic systems that identify, enrich, and engage the world's fastest-growing AI companies.

Your goal: replace manual "spray and pray" outreach with high-fidelity, signal-based automation that feels like a 1-to-1 human interaction but operates at 1-to-1,000 scale.

You will be part of a newly created team addressing Greenfield AI & Digital Natives account - reporting to the Head of High Velocity Sales

Build the AI GTM Operating System — From Zero

• Co-architect and help build the end-to-end AI GTM stack in real-time alongside various stakeholders (Business Owners, AI Natives Manager, System & Tools, SalesOps, AI Innovation team, Growth Platforrm, and Engineering) - this is a live build, not a spec on paper (the Stack has been predefined and teams have been mandated to support)

• Ensure the tech stack if acting as a multiplier, with specific focus at the top of funnel until lead creation and human handover - addressing greenfield companies with the right angle

• Design, deploy, and iterate on agentic workflows tailor made for AI & Digital Natives plays - replacing deterministic, segment-level plays with fluid, account-level orchestration

Bridge Sales, Growth Platform & Engineering

• Serve as the connective tissue between HVS Sales (execution), Sales Acceleration & Innovation (SalesTech/CRM), Growth Platform (KYC scoring, Post Office orchestration, WAC onboarding), and Software Engineering — translating business intent into technical builds and vice versa

• Partner directly with Growth Platform engineers to integrate first-party product telemetry and propensity models into the AI GTM so outreach is triggered by signal, not schedule

• Work with Systems & Tools, as well as SalesOps to ensure Salesforce remains the clean system of record while opening it up as the data foundation for the rest of the stack

Operate and Scale the Stack

• Activate and run the autonomous GTM day-to-day: deploy prompts, monitor agent performance, tune orchestration rules, and escalate only when the system needs human judgment

• Start focused on AI Natives (~20k greenfield + free accounts), then extend to SMB Sales — build once, scale many

• Measure what matters: Cost per Inference (CPI), attributed pipeline, "Signal Detected" → "Meeting Booked" → "Opportunity Created" conversion, and % rep time recovered for high-value conversations

Multiply the Sales Team

• Act as a multiplier: Leverage the AI GTM Stack to ensure full coverage of the TAM, right touchpoints based on expected customer needs and propensity, leveraging AEs and Inside Sales to maximize their impact in the customer lifecycle until Closing

• Build proactive co-pilot surfaces (bots, dashboards, alerts) powered by intent and scoring signals so reps spend 70%+ of their time on value-based conversations and closing, not admin

• Enable Inside Sales and AEs with real-time competitive intelligence, personalized discovery guides, and auto-generated proposal decks grounded in account-specific data

Rapid Experimentation & Pioneer the Playbook

• Run weekly experiments on signals, hooks, timing, channels, and agentic behaviors — iterate relentlessly in a 0→1 motion with no legacy playbook and no glass ceiling on optimization

• Document and scale repeatable AI GTM plays: what starts in AI Natives must become the blueprint for how Atlassian sells at velocity to greenfield targets

• Feed learnings back into Growth Platform, Product Marketing, and Pricing (VC credits, marketplace programs, startup perks) to sharpen the AI Natives value proposition and commercial model

Think Beyond — Shape the Future GTM

• Evaluate and integrate external AI GTM providers alongside internal capabilities, recommending build vs. buy at each layer

• Stay at the frontier of agentic AI: bring outside-in perspective on what's possible, pressure-test the roadmap, and ensure Atlassian's AI GTM stays ahead of the market

Must-Have

• 3+ years in Growth Engineering, Revenue Operations, GTM Engineering, or a technical AE role at a high-growth SaaS or AI company

• Technical proficiency: comfortable with APIs, JSON, webhooks, and basic scripting (Python or JavaScript). Not a full-stack engineer, but a "power user" of automation platforms

• Hands-on experience building automated outbound workflows

• AI-native mindset: early adopter of LLMs and agentic workflows; knows how to prompt-engineer for high-quality, non-robotic output

• GTM intuition: understands the sales funnel, knows what makes a good hook, and can define an ICP for a technical audience

• Data-driven: designs experiments, measures outcomes, optimizes relentlessly

Nice-to-Have

• Experience selling to or working within AI-native / developer-first companies

• Familiarity with Atlassian products (Jira, Confluence, Bitbucket, Rovo) and the developer/IT buyer persona

• Experience with Salesforce administration

• Background in PLG + sales hybrid motions (product-qualified leads, PLS)

• Prior work at Clay, Copy.ai, Apollo, Instantly, Outreach, or similar GTM tooling companies