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Currently available for select engagements

Hire AI Agent Developer for Marketing Agencies
Senior, direct, no layers

An AI agent developer builds agents that do work, not just answer questions: qualifying inbound enquiries, triaging requests, chasing approvals, and updating your systems, with a human in the loop where stakes are high.

15+
Years Experience
100+
Projects Delivered
6
Countries Served
$25M+
Revenue Enabled
Marketing Agencies — AI Agent Developer

A senior ai agent developer for marketing agencies

Marketing agencies sell outcomes, but their own operations are often the least systematised part of the business. Each client arrives with a different stack — one on HubSpot, one on Salesforce, one on a spreadsheet — and the agency absorbs that variety by hiring more account managers and building more one-off reports. Growth adds clients, but it adds the same amount of manual work, so margins flatten exactly when the agency looks busiest.

The second problem is proof. Retainers get questioned the moment results wobble, and an agency that cannot show, in the client's own numbers, what changed and why, is negotiating from weakness. Dashboards that nobody opens and monthly PDFs that nobody reads do not protect a retainer; a clear, shared record of work and results does.

An AI agent developer builds agents that do work, not just answer questions: qualifying inbound enquiries, triaging requests, chasing approvals, and updating your systems, with a human in the loop where stakes are high. For marketing agencies, that means the repetitive coordination — intake, follow-up, status chasing — handled reliably around the clock, while your team handles the judgement calls. I am Omer Muneer Qazi, with 15+ years of experience and 100+ projects delivered. Browse the full hire hub for related engagements, or book a free discovery call and we will test the fit before any scope is agreed.

What you get

What this engagement covers for marketing agencies

  • Support and intake agents — agents that answer, qualify, and route from your own docs and systems, escalating to a human on low confidence or high value.
  • Workflow agents — agents that run multi-step operations: triage, data entry, approvals, and follow-ups across the tools you already use.
  • Grounded in your content — retrieval over your docs, policies, and catalogues, so answers cite your sources instead of inventing them.
  • Tool use and guardrails — function calling with permissions, rate limits, and refusal rules, so an agent can act without acting recklessly.
  • Evaluation before launch — test sets built from real conversations and real cases, scored for accuracy and escalation quality before anything goes live.
  • Observability and handover — conversation logs, cost tracking, and failure review, so the agent improves weekly instead of drifting.
Working in Marketing Agencies

Built for how marketing agencies actually work

Tools and systems. The agency stack is well established, and builds must respect it. HubSpot and Salesforce cover CRM and marketing automation for most clients; reporting is assembled in AgencyAnalytics or Looker Studio; search work leans on Semrush and Ahrefs; paid media runs through Google Ads and Meta Business Suite; email through Mailchimp or the client's own platform; delivery is coordinated in Asana, Monday.com, or Slack. A new tool that duplicates one of these instead of connecting to it will be abandoned within a quarter.

Where the work pays off. The highest-value work is connective: a client onboarding flow that captures logins, brand assets, and goals once and provisions every system from it; a reporting layer that translates platform metrics into the client's business language; content and campaign workflows where approvals, publishing, and results live in one place; and a delivery record that makes the next quarterly review a conversation about results instead of a defence of the retainer. The agency's craft stays creative and strategic; the administration around it stops scaling linearly with headcount.

How it works

From kickoff to delivery

  1. Pick one job

    One agent, one job, one success metric, chosen from where your team actually spends hours on coordination.

  2. Connect your data and tools

    Wire docs, CRM, and ticketing, set guardrails and escalation rules, and define the human handoff.

  3. Evaluate and harden

    Run the test set, fix the failures, and prove accuracy and cost per conversation before launch.

  4. Launch in slices

    Go live to a portion of traffic, review logs weekly, and expand scope only on evidence.

Why Omer

Why hire Omer

  • Senior-only delivery: one person owns the ai agent developer work, its integrations, and its handover.
  • Built for production, not demos: permissions, monitoring, and documentation from day one.
  • Direct communication: no account-manager layer between you and the person doing the work.
  • Measured on outcomes: agreed metrics reviewed regularly, with scope adjusted on evidence.
  • No lock-in: your code, your data, your accounts, documented for handover.
FAQ

Questions, answered

Can you connect to each client's different stack?
Yes, that variety is the point. Builds use each client's existing CRM and ad platforms — HubSpot or Salesforce, Google Ads, Meta Business Suite, Mailchimp — through their official APIs, with a shared internal layer so the agency team works one way regardless of which client they are serving.
Will this actually protect retainers?
It gives the agency something a retainer review can stand on: a shared, current record of work delivered and results achieved, in the client's own metrics, updated without manual report-building. That does not guarantee renewal, but it removes the most common reason retainers are questioned — nobody could see the value.
How do you avoid adding yet another tool the team ignores?
By building into the tools the team already opens every day — Asana or Monday.com for delivery, Slack for approvals, AgencyAnalytics or Looker Studio for reporting — instead of launching a separate portal. Adoption is measured after launch, and anything unused gets cut.
How is an agent different from a chatbot?
A chatbot answers. An agent acts: it uses tools, follows multi-step rules, and completes work, escalating to a human when confidence is low or stakes are high.
Will it hallucinate to our clients or audiences?
It is constrained to retrieved sources and explicit refusal rules, with escalation on anything uncertain. Evaluation before launch measures exactly this, on your real cases.
Currently available for select engagements

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