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Lorikeet
Marketing & Sales 5h ago

Demand Generation Lead

Lorikeet
United StatesUnited States
Full-time
Not Disclosed
Mid-Level

Job Description

Key Skills Required

Master these to land this role

B2B SaaSPipeline DevelopmentLead GenerationSalesAI

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About the role and you

We're hiring a Demand Generation Lead to own pipeline generation for North America. Today, demand gen at Lorikeet is spread across several people who each carry a piece of it alongside their day jobs β€” this role exists to change that. You'll be the first person whose sole focus is building the machine that fills our pipeline.

You'll own a North American pipeline target and work backwards from it β€” designing and executing the mix of events, webinars, industry programs, and campaigns that gets us there. You'll also help shape how demand gen scales as a function as we grow, defining the playbook rather than inheriting one. This is a mid-senior role for someone who's comfortable being accountable to a hard revenue-linked number with a high degree of autonomy over how they hit it.

What you'll do

  • Own the North American pipeline target and build the quarterly plan that gets us there

  • Design and run the full demand gen program mix: field events, executive dinners, webinars, industry programs, and integrated campaigns

  • Work backwards from pipeline goals to channel-level targets, budgets, and forecasts, and report clearly on what's working and what isn't

  • Partner closely with Sales to ensure every program converts β€” tight handoffs, fast follow-up, and shared accountability for pipeline quality

  • Build the demand gen operating infrastructure from scratch: campaign tracking, attribution, and reporting that give us a real view of the funnel

  • Identify which channels and plays are worth scaling and which to kill, iterating quickly with limited resources

  • Define the demand gen playbook for Lorikeet as we grow, laying the foundation for the function's future team and budget

The right candidate

We're looking for someone who is energized by owning a number, not just running programs β€” someone who sees a pipeline target as a puzzle to reverse-engineer rather than a burden. The ideal candidate learned the fundamentals of demand gen inside a rigorous, well-resourced marketing org, then proved they could build the whole thing from scratch with none of that scaffolding.

You might be a fit if you:

  • Have 4–7 years of demand generation experience in B2B SaaS

  • Spent your foundational years at a public software company where you learned what best-in-class demand gen looks like

  • Then spent 2–3 years at an early-stage startup (under ~100 people) building the demand gen function from zero β€” choosing channels, setting up systems, and owning outcomes without a big team or budget

  • Have hands-on experience across the program mix: field events, webinars, executive dinners, and industry programs, not just digital campaigns

  • Think in pipeline, not MQLs β€” you work backwards from revenue targets and can defend your math

  • Operate with high autonomy and low need for direction, and are relentless about follow-through

  • Care about the quality of the pipeline you create, not just the volume β€” you see Sales as your customer

  • Are curious about AI and excited to help define what an AI-first company looks like from the inside

What's unique about this opportunity?

  • A culture that's genuinely different. Low ego, high trust, no tolerance for talented jerks. We work efficiently, keep hours flexible, and actually mean it β€” because life outside work matters. We're committed to building a diverse team and actively encourage applicants from underrepresented backgrounds. We care far more about user obsession and eagerness to learn than traditional credentials.

  • A front-row seat to building something meaningful. We're Series A and moving fast. You'll have real scope to shape the product and the company β€” not just execute someone else's vision.

  • Performance recognized in real time, not on a calendar. Promotions happen when you're ready β€” leadership meets every six weeks specifically to identify and recognize strong performers, so you're never waiting for an arbitrary review window to move up.

  • We're AI-native, and we'll make you AI-native too. Every person at Lorikeet uses AI in their day-to-day work (current favourite: Claude Code), with unrestricted access and no usage limits. You'll leave with skills that matter for the next decade of work.

  • Twice a year, the whole company flies to Hawaii. Headquartered in Sydney, with teams spanning the US and UK β€” which means getting everyone in the same place is something we invest in seriously. We spend the time hacking on ideas, building things together that wouldn't otherwise exist, and making memories that remind you why you joined a startup in the first place.

  • A recruitment process built on respect, not hoops. We keep it simple: a couple of informal chats to share our story and hear yours, followed by a paid ~two-day work trial. The work trial is genuinely the best part β€” you'll work on real problems alongside the actual team, get a true feel for how we operate, and we'll both come out of it knowing whether this is the right fit. No trick questions, no take-homes that disappear into a void. Just real work, done together.

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Lorikeet (operating under lorikeetcx.ai, legally Lorikeet CX, Inc., formerly known as Optech) is the premier, enterprise-grade Agentic Customer Experience (ACX) platform, customer service AI pioneer, and automated workflow orchestration powerhouse engineered to serve as the definitive, high-velocity omnichannel resolution, customer intelligence, and digital interaction layer for scaling global brands, fintechs, and highly regulated healthtech systems. Founded by product and AI research visionaries Steve Hind (former product lead at Stripe and Watershed) and Dr. Jamie Hall (former Google Brain research tech lead and co-author on the landmark LaMDA and Meena AI papers), the company completely eliminates the severe systemic friction of modern enterprise customer supportβ€”where expanding organizations encounter crippling ticket volumes, high agent overhead, and basic chatbots that merely summarize help centers without solving actual customer issuesβ€”by deploying a sophisticated, multi-agent reasoning matrix. Moving far beyond traditional, passive decision-tree scripts or loose retrieval-augmented generation (RAG) models prone to hallucinations, Lorikeet natively unifies an Intelligent Graph architecture that strictly executes complex standard operating procedures (SOPs), multi-turn programmatic workflows, direct secure API action hooks to deep corporate back-ends (like Zendesk, Stripe, Shopify, and on-chain crypto networks), and real-time Voice AI infrastructure into a single high-availability, no-code AI concierge workspace. Solving tickets end-to-endβ€”such as managing delayed e-commerce deliveries, processing multi-step financial refunds, and troubleshooting complex blockchain transactionsβ€”the system slashes chat first-response times from 30 minutes to under 60 seconds with 99% execution accuracy. Trusted by customer-obsessed high-growth brands including Airwallex, Linktree, Eucalyptus, Remote.com, and Flex, the platform has scaled rapidly across international footprints. Valued as an elite rising star in the conversational AI landscape, the firm has raised over $49 million in total elite institutional venture capitalβ€”anchored by a major Series A growth execution led by QED Investors alongside heavy participation from Square Peg Capital, AirTree Ventures, Blackbird Ventures, King River Capital, Skip Capital, and executives from OpenAI, Stripe, and Atlassian. Under the hood, its technology core utilizes advanced intent-recognition models, real-time multi-agent orchestration loops, and strict role-based access controls designed to isolate risky activities like account cancellations behind dynamic gating parameters without reducing live production velocity. What sets Lorikeet apart is its uncompromising dedication to replacing passive, informational chatbots with absolute real-world resolution predictability, deep system integrations, and multi-channel customer satisfaction; by bridging the gap between performance-intensive structural back-office data and natural, human-quality consumer interactions, the enterprise remains a definitive cornerstone of modern algorithmic customer support infrastructure and global AI business transformation.

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