The role

You own the Meta Methodology: how Meta Ads should be run, encoded as the deterministic rules and skills the agent runs across the whole client portfolio. Inside the agent it becomes the algorithm. It's an individual-contributor seat, closest to the product.

For this role, "done" means

• We have an algorithm that runs Meta media buying end to end from a set of inputs: goals (target CPA/ROAS, budget), parameters, and creatives.
• We generate hypotheses to improve the algorithm, test them, and keep what works.
• We have skills to audit, implement, adapt, and control the algorithm as the skills and rules for a specific account.

So on the same creatives and landing pages or apps, our algorithm beats manual media buying, and we can prove it.

What you'll do

• Own the single source of truth: one written methodology that everything else follows, plus the rules and skills that encode it.
• Improve the methodology: define how to value the gain or loss from each action or inaction on an account, generate suggested changes to the methodology that could improve results, and test them on historical data.
• Build the testing machine: design and run tests by hand with the agent, then a testing skill that speeds up every step of the testing cycle, then a testing loop that runs cycles autonomously and generates improvements for review.
• Make it implementable: an account audit skill that account managers and AI marketing engineers use to check each account against the methodology for differences and improvements. Implementation skills that create and adapt every skill and rule for a new client. Plus the control skills, automations, and loops that keep it running.

Who we're looking for

We're looking for top-1 experts on Meta methodology, ready to put it inside the agent, and we need unicorns in this position. This role stays open until we find them all.

Must-have

• You built your own methodology, and it has worked at scale. You have a vision of how ideal Meta media buying should be built, and you've run media buying on it for large accounts at ~$500K+/month. At that volume you know Meta from the inside: account architecture, creative testing, data analysis, and thresholds. One approach held across accounts, and you kept refining and researching it. A good marker: large clients buy your time for consulting on media buying methodology.
• You dig down to the mechanics and keep tuning. Every new task – a piece of decision logic, a metric, channel behavior – you break down to the mechanics and improve against historical data. This way of thinking is the core of the role.
• You've built decision logic past simple rules. Combined metrics and rule cascades at fine granularity, each priced by the expected value of acting or holding back.
• AI-native, you build it yourself. You build the pipelines and automation by hand (vibe-coding rules, wiring models) and turn your logic into deterministic skills, backtested before they ship.

What you'll get

• You join a team of top performance marketing and product experts. Our team came from the biggest performance marketing agencies and from the ad platforms: Meta Ads, Google Ads, and TikTok Ads. You work directly with the product and with our founders, Seva Ustinov and Kirill Kasimskiy, who built and scaled a performance marketing agency to 100+ people, then a full-funnel marketing analytics platform, and rebuilt their own team around AI agents.
• Access to the strongest media buying teams on the market. You work with the Heads of UA and CMOs behind $300K–$15M a month, and with the AI marketing engineers running those accounts.
• A machine built around your methodology. You research and test hypotheses on historical data, then ship what works as rules and skills. AI marketing engineers run your methodology on real client accounts, with their data, their business context, and their own media buying playbook, and bring back the use cases: what works, and the edge cases. Experts in the industry share what works with you. You test what comes back, standardize what holds, and ship again. The agent and the team scale your refined rules and skills across the portfolio, and the product team keeps building out the agent so all of this can run.
• An AI-first team. Every function runs on agents in a shared workspace: engineering, sales, ops, customer projects. We show you how to use and build them day-to-day, and how to put your expertise inside.

Compensation and conditions

• Compensation. Up to $180,000 a year gross, based on skills.
• Remote, worldwide. You can work remotely from anywhere in the world, as long as your timezone is no further east than UTC+5: the Americas, Europe, Africa, the Middle East, and Western/Central Asia all work.
• Tools and infrastructure. We provide a laptop, software, and any other tools necessary for work, including any AI tools that help you: Cursor, Claude, and Codex plus our shared AI infrastructure are the baseline.
• Education. We cover 50% of the costs of relevant educational activities.
• Vacation. Two weeks twice a year, plus holidays.
• Employment. Via a Deel contract.

How to apply

1. Application . Click "Apply for this role" button and fill in the form with your social media links and contacts. We'll answer you from recruiter@plurio.ai within two days.
2. We'll get back to you with the next steps.
3. Interview with the leadership team.
4. Offer.