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Salary: USD 340,000 - 390,000 / annual
Attentive is building the next generation of autonomous marketing agents—systems that will transform how brands plan, execute, and optimize their marketing. As Director of Engineering for the Marketing Agent Platform, you'll lead the engineering team building the core systems that power this vision.
In this role, you'll work at the intersection of agentic planning, real-time behavioral signals, platform capabilities, experimentation, and reliable execution at massive scale. You'll be responsible for the engineering systems that enable autonomous decision-making: who should receive a message, what it should say, when it should send, which offer to include, and which channel to use. Your work will help turn increasingly sophisticated AI systems into dependable products capable of making and acting on millions of marketing decisions.
The scope extends beyond Attentive's own channels. Through APIs and MCP, you're building toward a future where this intelligence operates across a brand's broader marketing stack, including external email providers, advertising platforms, websites, and custom agents. This is an opportunity to evolve Attentive from a platform that powers messages into one that coordinates and continuously improves a brand's broader marketing program.
You'll manage a team of engineers, set the bar for talent and execution, and bring strong technical opinions paired with curiosity to challenge assumptions. You'll partner closely with product, ML, and data science teams, understanding what models need from the platform without needing to own the models themselves. You'll own the technical direction and roadmap, not just execute predefined tasks.
Attentive sends billions of messages annually for 8,000+ brands, driving tens of billions in customer revenue. The company is recognized as the #1 SMS marketing provider by G2, included in Deloitte's Fast 500 (four years running), Forbes' Cloud 100 (five years running), and has a distributed global workforce with hubs in New York, San Francisco, London, and Sydney.
REQUIREMENTS:
- 3+ years managing engineers; 8+ years total engineering experience
- Demonstrated engineering excellence at a top-tier organization
- Experience building large-scale reinforcement learning systems (data, infrastructure, and serving platforms); background from frontier labs, AI-native companies, AI labeling companies (Handshake, Mercor, ScaleAI), or tech companies with production-grade RL systems
- Fluency at the interface between product engineering, ML, and data science; ability to be a real partner without owning the model
- Shipped agentic or LLM-backed systems; understands production tradeoffs of tool use, orchestration, and retrieval
- Strong expertise in distributed, data-heavy systems: streaming, event-driven, cost-aware inference
- Tracks the AI field closely; knows what shipped last quarter and why it matters
- Still writes code
- Hires well, gives direct feedback, holds high performance bar, builds accountability
- Experience building intelligent systems at massive data scale
- Startup mindset in a scaled environment: move quickly, embrace ambiguity, take ownership
