About the role
We're looking for someone who lives at the seam between AdTech operations and engineering. You'll be our eyes and hands on the supply side, watching exchanges for signal, spotting issues before partners notice them, and turning what you see into AI-assisted systems that scale. You'll be the technical face of Arpeely to exchanges and clients, and you'll work shoulder-to-shoulder with Engineering and Data Science to ship the tools you need.
This role suits someone who is equally comfortable reading a network waterfall in DevTools, writing a Python and SQL script and shipping small apps with Claude\Cursor, and walking a partner through an integration issue on a call.
What you'll do
- Build AI systems. Design and ship AI Agents that monitors supply, watches integrations, and runs compliance and creative review at scale. This is the core of the role: turning what you see into systems that work while you sleep.
- Monitor exchange supply for anomalies, signal, and revenue opportunities: pricing shifts, new inventory, traffic-quality changes, integration regressions.
- Own ad quality. Track critical rendering, viewability, latency, and creative-integrity metrics across our buying surface; triage and drive fixes when something breaks.
- Hunt commercial upside. When you spot something interesting in the data (a misconfigured deal, an underpriced supply path, a new format taking off, a partner leaving money on the table), turn it into a business action. We expect this role to pay for itself many times over.
- Be the technical POC to exchanges and clients (Google, AppLovin, and others). Own integration health, debug protocol-level issues, translate between their stack and ours, and represent Arpeely in technical conversations.
- Partner with Engineering and Data Science. Surface what you see in the wild into requirements, dashboards, and models; co-build the internal tools you'll use.
- 3–5 years in AdOps, AdTech, programmatic operations, technical account management, or a closely related role.
- Strong network and web-debugging chops. You are well familiar with the OpenRTB formats. You can open DevTools and reason about cookies, DOM, redirect chains, network requests.
- AdTech domain fluency. You understand attribution, OpenRTB, VAST/VPAID, SDK vs. web integrations, viewability, brand safety, supply paths, and the difference between an exchange, an SSP, a DSP, and an ad server.
- Scripting and AI comfort. Python or JavaScript, enough to wrangle data, automate checks. You don't need to ship production code, but you should be able to prototype.
- AI-native working style. You reach for agents to accelerate yourself; you've built or scaled at least one workflow with them.
- Communication that works in two directions. Clear and credible with exchange partners and clients, and equally clear with engineers and data scientists internally.
- Business sense. You don't just report problems; you frame them in terms of revenue, risk, and opportunity, and you push for outcomes.
Nice to have
- Prior exposure to OpenRTB, ads.txt / sellers.json, IAB standards (MRAID, OMID, VAST), or prebid.
- Experience working directly with Google AdX / Authorized Buyers, AppLovin, Unity, Magnite, Index, PubMatic, or similar.
- SQL fluency and comfort poking around large event logs (BigQuery, Snowflake, Athena, or similar).
- Experience designing or operating creative-review or compliance pipelines.
Skills Required
- 3-5 years in AdOps, AdTech, programmatic operations, or technical account management
- Strong network and web-debugging skills (Browser DevTools, DOM, cookies, redirect chains, network requests)
- Fluency with AdTech concepts (attribution, supply paths, viewability, brand safety, exchanges/SSP/DSP/ad server)
- Familiarity with OpenRTB formats and protocol-level debugging
- Scripting ability in Python or JavaScript to prototype and automate checks
- AI-native working style; experience building or scaling at least one agent/workflow
- Clear technical communication with external partners and internal engineers/data scientists
- Ability to translate technical issues into business impact and drive outcomes
- SQL fluency and experience querying large event logs (BigQuery, Snowflake, Athena)
- Experience with VAST/VPAID, MRAID, OMID, ads.txt / sellers.json, or Prebid
- Experience working with Google AdX, AppLovin, Unity, Magnite, Index, PubMatic, or similar exchanges
- Experience designing or operating creative-review or compliance pipelines
What We Do
We build and operate Machine Learning based media acquisition algorithms for managed & RTB environments. Our autonomous media engine, targets, re-targets, self-adapts and generates insights to zero-down on the most valuable traffic, users and LTV. Directly connected to Ad-exchanges, it's able to predict, detect and evade fraudulent sources & low intent traffic, generating additional market edge. Arpeely is a fusion of Engineering, Fraud Sciences, AI, Data Science, and Digital Marketing








