Job Details

VP of Engineering

AI-Driven Marketing Optimization Platform

Overview

Our client is building the AI-enabled marketing platform of the future — a unified operating system that integrates creative, media, data, and performance into a singleAI platform . Through a combination of high-performing agencies and a proprietary AI platform (DMOS – Digital Marketing Operating System), the client is engineering a new model for brand and agency growth.

The platform leverages a swarm architecture of specialized AI agents — creative agents, media agents, analytics agents, and optimization agents — working in concert under human supervision. We are not building incremental SaaS tools; we are building an AI-Amplified Operating System that compresses feedback loops, increases marketing ROI, and scales senior marketing talent at software speed.

Backed by experienced operators, investors, and agency leaders, the company combines real revenue, real clients, and a real platform roadmap. This is a rare opportunity to build an enterprise-grade AI-native platform inside an already scaled services ecosystem.

Core Mandate

Build and ship a production-grade AI platform that:

• Reliably manages multi-agent workflows
• Handles enterprise-scale marketing spend
• Iterates rapidly on real customer feedback
• Balances speed with system reliability

What Success Looks Like — First 12 Months

• A working production system used by real customers
• Reliable multi-agent workflows with no catastrophic failure modes
• High iteration velocity (weekly or bi-weekly shipping cadence)
• A strong early engineering team of 5–8 people
• Clear product traction and customer engagement

Key Responsibilities

Architecture & Systems

• Own end-to-end technical architecture of the AI-Amplified Operating System.
• Design and manage agent optimization frameworks
• Establish infrastructure for agent lifecycle management, version control, and benchmarking.
• Build secure, enterprise-grade data pipelines and integrations across media, CRM, analytics, and creative tools.
• Implement cost controls and LLM optimization strategies for scalable margin performance.

Agent Development & QA Discipline

• Operationalize hypothesis-first agent development and benchmark-driven validation.
• Build internal QA frameworks for behavioral validation, adversarial testing, and safety controls.
• Deploy progressive autonomy systems (human-in-the-loop ? supervised automation ? controlled autonomy).
• Ensure observability across agent decisions, outputs, and impact on campaign performance.

Product & Iteration

• Work directly with customers to refine the product
• Ship quickly and iterate based on real feedback
• Balance MVP speed with the reliability standards enterprise customers expect

Team Leadership & Scale

• Recruit, lead, and develop a high-caliber engineering organization (AI, full-stack, infra, QA).
• Establish sprint velocity, 2-week iteration cycles, and measurable KPIs.
• Partner with Product to prioritize high-leverage workflows across agencies.
• Prepare the platform for external SaaS commercialization (Phase 2 & 3 roadmap).

Strategic Impact

You will be responsible for transforming the company from an AI-enabled agency network into a defensible, AI-native marketing platform company. This role directly impacts enterprise valuation, scalability, and long-term category leadership.

Required Experience

• Ad tech or marketing technology — 0?1 experience strongly preferred
• Deploying AI/LLM systems to production
• Multi-agent or orchestration workflows
• Strong backend and distributed systems fundamentals
• Leading engineering teams of 5–20 people
• Hands-on coding — this is not a purely managerial role

Preferred Background

• Experience at companies such as Tapjoy, The Trade Desk, Pixis, Smartly.io, or Northbeam
• AI-native SaaS or adtech companies
• High-growth startup environments

Key Traits

• Builder mindset — not a pure manager
• High technical rigor
• Mentally flexible; not dogmatic about tools or frameworks
• Customer-focused
• Moves fast, but cares about quality

Location

Preferred: New York or Los Angeles

Open to: San Francisco or remote for exceptional candidates