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Salary: USD 340,000 - 390,000 / annual
Attentive is an AI marketing platform that unifies SMS, RCS, email, and push notifications to deliver personalized customer experiences at scale. The company powers billions of messages annually for 8,000+ brands across 70+ industries, driving tens of billions in revenue for customers.
You will lead the engineering team building the next generation of Attentive's decision-making system: an autonomous marketing agent that transforms how brands plan, execute, and optimize their marketing. Marketers will set goals and boundaries while the platform develops strategies, takes action, measures results, and continuously improves. Your work sits at the intersection of agentic planning, real-time behavioral signals, platform capabilities, experimentation, and reliable execution at massive scale.
As Director of Engineering, you will:
- Build engineering systems that enable autonomous marketing agents to make and act on millions of marketing decisions reliably
- Work across agentic planning, real-time data signals, platform capabilities, experimentation frameworks, and large-scale execution
- Lead the technical vision for expanding this intelligence beyond Attentive's channels through APIs and MCP to operate across brands' broader marketing stacks (email providers, advertising platforms, websites, custom agents)
- Evolve Attentive from a message-delivery platform into one that coordinates and continuously improves entire marketing programs
- Manage and develop a high-performing engineering team, setting ambitious talent and execution standards
- Partner closely with product, ML, and data science teams to translate model requirements into platform capabilities
- Own technical decisions on distributed systems, data-heavy infrastructure, streaming, event-driven architecture, and cost-aware inference
You will have meaningful influence over team composition, architecture, technical direction, and roadmap—not just execution of predefined tasks. This is one of the company's biggest strategic bets with visibility to senior leadership and the board.
Requirements:
- 3+ years managing engineers; 8+ years total engineering experience
- Demonstrated experience building engineering excellence at a top-tier organization; ability to hire and lead A+ teams with strong technical opinions and intellectual curiosity
- Experience building large-scale reinforcement learning systems (data, infrastructure, and serving platforms—not just ML models); background from frontier labs, AI-native companies using RL for fine-tuning, AI labeling companies (Handshake, Mercor, ScaleAI), or similar
- Fluency at the interface between product engineering, ML, and data science; ability to understand what models need from platforms without owning the model itself
- Shipped agentic or LLM-backed systems in production; deep knowledge of tool use, orchestration, and retrieval tradeoffs
- Strong expertise in distributed, data-heavy systems: streaming, event-driven architecture, cost-aware inference
- Tracks AI/ML field developments closely; understands what shipped recently and why it matters; willing to kill own work when better solutions emerge
- Still writes code; hires well; gives direct feedback; maintains high performance bar; builds accountability without drama
- Expertise in AI at massive data scale, translating rich behavioral data into better decisions
- Startup mindset within a scaled environment; moves quickly, embraces ambiguity, takes ownership
- Energized by high-impact ownership and technical/product leadership with real influence over strategy
