AI Growth Manager Ads

Description

About lemlist

lemlist is the AI-powered sales engagement platform helping sales teams build pipeline smarter, not harder.

Bootstrapped from day one, we’ve grown from 0 to $50M+ ARR in 8 years without raising a single dollar. Today, 40,000+ sales teams use lemlist to book more meetings and close more deals.

We’re building the next generation of outbound: AI-first, multi-channel, highly personalized, and deeply integrated into the way modern sales teams work.

And we’re just getting started.

We are hiring an AI Growth Manager, Ads to double our paid acquisition: €1M spent in 2026 → $2M/year, driving signups, purchases and expansion.

Paid is already our 2 revenue channel, and we're probably using 1% of it. Our competitors spend up to 10x more than us. We've been too bottom-funnel and way too careful.

So we made the call: paid is a PLG channel. Think subscription-app playbook for B2B SaaS → hundreds of creatives a month, ad → free trial → purchase, ROAS to the cent, and ads that create demand on top of catching it.

You'll own the whole thing. Meta and Google today, YouTube, TikTok, Reddit and ChatGPT ads next. Big budget, full ownership, zero media buyers. You'll build the agents that let one person run what most companies staff with five.

You'll report to Erwan (VP Growth) and work with Lifecycle, Website, Influence and the GTM Club.

What your impact will look like

Within 3 months, you'll have:

Taken over Meta and Google Ads end to end, audited both and shipped a V1 strategy (audiences, funnels, angles, budget ramp-up by geo)

Rebuilt tracking so every creative, landing and geo is measured from click to first payment

Launched the creative engine (creators, AI, UGC) → 200+ creatives shipped in a month

Plugged Adkit (already live on Google) into Meta and shipped your first agents: daily perf in Slack, creative briefs fed by reviews and competitor ads, auto-rules

Tested one new channel: YouTube, TikTok, Reddit or ChatGPT ads

Within 12 months, you'll have:

Scaled paid to a $2M/year run rate with LTV/CAC above 6

Hit 500+ creatives a month, half new concepts, half iterations on winners

Handed 80% of day-to-day ops (launches, copy, keywords, reporting) to agents you built

Given every geo × persona × use case its own hooks, ads and landing, all tracked

Tested 3+ new channels and turned at least one into an evergreen program

Built one measurement framework everyone trusts: signup → paid → expansion

Bonus: shared your playbooks publicly on Linkedin

Responsibilities

• Build the system first
• Map what running paid at lemlist really looks like day to day, spot what's slow or broken, automate it
• Build agents that brief, produce, launch, analyse and iterate, and get better every week. Stack: Adkit, Claude, Storyblok + Meta + Google Ads MCPs
• Your weekly question: "how does this run without me, and how does it learn?"
• Own paid end to end
• Meta first, Google right behind
• Audience first, channel second: find where our buyers hang out, then pick YouTube, TikTok, Reddit, ChatGPT ads or whatever comes next
• Run campaigns across channels with one message and one funnel
• Run the creative engine
• Build a creator pool (paid per creative or on perf) + AI production + agencies
• 400–500 creatives a month: 50% new, 50% iterations on winners, 3–5 hooks per concept
• Turn everything we produce (GTM Club videos, influencer posts, webinars) into ads. Kill losers fast, milk winners until they die
• Write ads people actually click
• Thumb-stoppers that stand out in a feed full of AI SDR ads
• Emotional and MOFU angles: traction, quotas, commissions, "how do I close my first 50 customers?"
• Our customers' words, pulled from G2 reviews, sales calls and prospect replies
• On Google, copy that matches what people really type. They search like they prompt ChatGPT now
• Steal ideas from fashion, sport and food brands. Never from our competitors
• Ship your own funnel
• One ad, one hook, one landing. You build and A/B test them yourself
• You own tracking: events, Conversions API, attribution
• No engineering queue. You have Claude, the MCPs and access to everything
• Go granular
• Geo, persona, pain, use case, maturity: break everything down and track every variation
• Consolidated campaign structures so the algos learn, fully granular creatives and landings
• Own the budget and the results
• A $2M budget and its ramp-up plan
• Revenue is the only scoreboard. A signup that never pays doesn't count
• Bet big to learn fast. Price the downside before each bet, then cut or scale
• When a test wins, turn it into an evergreen program: set the bar it has to hold, automate it, and decide when it runs on autopilot or moves to a new owner
• Share your learnings every week

Conditions

Consumer growth DNA: you've scaled paid at a subscription app, a prosumer product or a hypergrowth PLG SaaS. E-com or mobile UA = big plus. We care about what you built, years don't matter.

Creative-obsessed: you've shipped hundreds of creatives a month and can walk us through your machine

AI-native: your skills, agents and automations run in production today

Full-stack: landings, tracking, A/B tests, you ship them yourself

Revenue-driven: you live in CAC, payback, LTV and ROAS

Sharp judgment: you know which test is worth running, and when the data (or the AI) is lying

Bold: spending too little scares you more than spending too much

Owner: you want this channel to be yours and you show up with a plan

Fluent in English

Bonus points

You've run a creator or UGC program paid on performance

You've scaled YouTube, TikTok or Reddit ads

You share your playbooks publicly and people follow you for them

Not for you if…

You need a team to execute

You stop looking after the signup

You launch 5 creatives a month and pray the algorithm does the rest

You open the competitors' ad library before starting anything

Interview process

Interview with Erwan (Vp Growth)

Use case & debrief avec Nicolas (Growth) et Domitille (CMO)

Team meeting with Hugo (Growth) & Lamia (Affiliates)

Interview with Charles (CEO)

Reference check

Offer