- Salary
- $340k – $390k
- Location
- New York, NY
- Type
- Full-time
- Department
- Engineering
- Seniority
- Director
- Source
- Greenhouse
Description
About the Role
Attentive sends billions of messages each year for more than 8,000 brands, helping drive tens of billions of dollars in revenue for our customers. Behind every message is a series of decisions: who should receive it, what it should say, when it should send, which offer to include, and which channel to use.
We’re building the next generation of that decision-making system: an autonomous marketing agent designed to transform how brands plan, execute, and optimize their marketing. Marketers will set the goals and boundaries, while the platform develops strategies, takes action, measures results, and continuously improves over time.
In this role, you’ll build the engineering systems that make that vision possible. You’ll work at the intersection of agentic planning, real-time behavioral signals, platform capabilities, experimentation, and reliable execution at massive scale. Your work will help turn increasingly sophisticated AI systems into dependable products that can make and act on millions of marketing decisions.
The opportunity extends beyond Attentive’s own channels. Through APIs and MCP, we’re building toward a future where this intelligence can operate across a brand’s broader marketing stack, including external email providers, advertising platforms, websites, and custom agents.
This is an opportunity to help evolve Attentive from a platform that powers messages into one that coordinates and continuously improves a brand’s broader marketing program.
What You’ll Accomplish
- 3+ years managing engineers, 8+ years engineering
- Has seen and helped build engineering excellence at a top-tier organization. Sets an ambitious bar for talent and execution, knows how to hire and lead an A+ team, and brings strong technical opinions with the curiosity to challenge their own assumptions.
- Has worked on building large-scale reinforcement learning systems (not the ML, but the data, infra, and serving platforms beneath it); examples of where you might find these engineers are from frontier labs, AI-native companies using RL for fine-tuning, AI labeling companies (Handshake, Mercor, ScaleAI), or other tech companies that have built web-scale production-grade reinforcement learning system
- Understands the interface between product engineering, ML, and data science, and is fluent enough to be a real partner. Understands what a model needs from the platform, without needing to own the model.
- Has shipped agentic or LLM-backed systems and knows the production tradeoffs of tool use, orchestration, and retrieval
- Strong on distributed, data-heavy systems: streaming, event-driven, cost-aware inference
- Tracks the field closely, has a real view on what shipped last quarter and why it matters, and has killed their own work when something better arrived
- Still writes code. Hires well, gives direct feedback, holds a high performance bar, and builds accountability without drama.
Your Expertise
- AI at massive data scale: You know how to build intelligent systems that take advantage of rich, high-volume behavioral data and translate it into better decisions and experiences.
- Startup mindset, scaled environment: You move quickly, embrace ambiguity, and take ownership while building within the resources and reach of an established Cloud 100 company.
- High-impact ownership: You’re energized by working on one of the company’s biggest strategic bets, with visibility and impact across senior leadership and the board.
- Technical and product leadership: You want meaningful influence over the team, architecture, technical direction, and roadmap, not just a predefined set of engineering tasks.
You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
For US based applicants:
- The US base salary range for this full-time position is $340,000 - $390,000 annually.
- Our salary ranges are determined by role, level and location
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