AI Creative Lead — Digital Marketing (India)

Anatta Design; United States; À distance; USD 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Remote-first environment

Résumé du poste

Anatta Design is seeking a strategist who can redesign how marketing work is produced by building an AI-enabled production engine around ideas, requests, and campaigns. You will create repeatable workflows across paid media, social, email, website, and presentations, turning loose requests into first versions quickly.

Expect to own the system: brand guidelines, tooling, and quality control, ensuring high-quality output at scale while dramatically increasing velocity and effectiveness for the

Description du poste

Why this role exists

AI has fundamentally changed how a small marketing team can operate.

We are not hiring someone because they can make things with AI. We are hiring someone who can redesign how marketing work gets done because they are an expert in AI. We do not need another person who produces creative faster. We need someone who can rethink the production system itself.

Your job is to take marketing ideas, requests, campaigns, sales needs and brand requirements and build an AI-enabled production engine around them. Sometimes that means generating an ad, a video, a presentation, a landing-page visual or a campaign concept. Other times it means creating a workflow that lets us produce the next fifty versions dramatically faster.

You will combine strong creative judgment with AI fluency, automation, experimentation and marketing instincts.

The goal is not more AI-generated content. The goal is dramatically more high-quality marketing output from the same amount of human effort.

If your instinct is that AI creative tools are a threat to craft, this is the wrong role. If your instinct is that they finally let you ship at the speed your ideas move, keep reading.

What you’ll own

You will turn marketing ideas into finished assets across paid media, organic social, email, website, sales enablement, presentations, video and other formats. You should be able to move from a loose request to a strong first version quickly, without requiring a perfect creative brief.

But producing the first asset is only part of the job. You should constantly ask: can this become a reusable system instead of another one‑off task?

You will design repeatable AI-assisted workflows for work such as:

• Paid media concept development and variant generation
• Campaign briefs and creative exploration
• Copy and messaging variations
• Social and email creative
• Video scripting, editing, repurposing and cutdowns
• Sales and pitch presentations - client-specific or pitch-specific decks turned around in hours, not weeks, and looking like Anatta made them on purpose
• Case study production
• Executive and thought-leadership content
• Landing-page assets
• Content repurposing across channels
• Brand and creative QA
• Research and creative inspiration

The expectation is not simply that you use AI tools. The expectation is that you make the entire marketing organization faster because you understand how to turn those tools into operating systems.

You also own three things that make the system hold:

• The brand system. Colour, type, logo usage, photographic and illustrative direction, motion language, deck templates, component libraries - codified into prompt libraries, style references, trained models and templates, so that quality is a property of the system and not of any single person’s afternoon.
• The toolchain. Knowing what the best available tool is this quarter, because it will not be the same one as last quarter. You test new tools on real work, keep the ones that earn their place, and can explain the trade-offs to non-designers.
• Quality control. Every asset that ships has your eye on it. AI gets you to 80% fast; the last 20% - the composition fix, the type correction, the hand with six fingers, the thing that is technically fine but is not us - is the actual job.

How we will measure success

We measure this role by leverage: how much high-quality marketing output and business impact one person can create through AI, automation, systems and strong creative judgment.

High production volume is only valuable if the work is useful, on-brand and driving results. Two hundred mediocre assets help no one. The goal is to increase the amount of high-quality marketing work the team can ship with the same or less human effort, while improving speed, consistency and performance.

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Measure

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What good looks like

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Quality and brand consistency

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Assets pass review on first pass; brand rules are documented well enough that others can follow them

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Creative contribution to performance

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Winning concepts identified and scaled; losing concepts killed fast; you can explain why an asset performed, not just whether it looked good

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Systems built

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Reusable workflows that make request #2 through #50 dramatically faster than request #1; measurable reduction in time-per-asset over time

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Throughput

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Sustained weekly volume of shipped, on-brand, useful assets across static, video and deck formats

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Turnaround

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Sales deck requests fulfilled same-day to 48 hours; ad variant sets in days, not weeks

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Video output

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Consistent monthly cadence of finished video and motion assets

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Tool leverage

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New tooling evaluated and adopted or rejected on a regular cadence, with the reasoning written down

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Hours worked, tools mastered for their own sake, and pixel-perfect one-off artistry are not on this list.

What you need to have

• A trained eye. You can look at a generated asset and say precisely why its wrong and what to change. This is the non-negotiable one - everything else can be learned faster than taste.
• Marketing judgment. You understand that an ad is not just a design. It has an audience, an offer, a message, a hook, an objective, a placement and a desired behavior. You understand offers, positioning, funnel stage and performance creative, and why an asset exists. You are curious about why creative performs, not simply whether it looks good. Without this, the output is gorgeous AI-generated garbage.
• Demonstrated AI-native production. A portfolio where a meaningful share of the work was produced with generative tooling - Claude, ChatGPT, Gemini, Midjourney, Figma, Veo, Runway and the like - and you can walk through how: the prompts, the references, the model choices, the post-production, the failures.
• Fluency across the current stack, or the proven ability to pick it up in days. For example: image generation and editing (Midjourney, Nano Banana / Gemini, Flux, Photoshop generative), video and motion (Veo, Runway, Kling, Higgsfield, After Effects, CapCut / Descript), voice and audio (ElevenLabs), decks (Figma, Google Slides, Gamma), asset and brand libraries (Kive or