Senior Software Engineer, Tag Engineering

Attentive is an AI marketing platform focused on 1:1 personalization, redefining brand and customer connections. The Senior Software Engineer for Tag Engineering will own the first-party data collection platform, working across various technologies to improve data collection and enhance performance.

Responsibilities:

• Own data collection across the full stack. Work across the JS tag, Cloudflare Workers, and Java backend services to deliver reliable first-party data collection at scale
• Expand what we do at the edge with Cloudflare Workers. Extend our Workers infrastructure beyond server-side tracking and proxy endpoints into tag serving, A/B configuration, and compute for agentic systems and data analysis
• Build agentic AI systems for data collection quality. Use heuristics and models from the ML team to identify poor data collection for specific customers. Build workflows that automatically diagnose and fix gaps, reducing the manual work that eats up engineering time today
• Improve the event ingestion pipeline. Strengthen the backend services that receive, validate, and route events from the tag. Make the pipeline more reliable and observable so engineers can trace data from collection through ingestion without guesswork
• Help lead technical direction on a small, autonomous team. Write proposals, run design reviews, and mentor teammates. With a team this size, your judgment directly shapes what gets built and how

Requirements:

• 6+ years of professional software engineering experience, with a track record of working across multiple layers of a system, not just frontend or backend alone
• Backend experience building and operating services in Java, Kotlin, or a similar typed language, including API design, data modeling, and testing
• Comfortable with JavaScript/TypeScript beyond casual use. You can reason about browser runtime behavior, async patterns, and performance in production
• Experience with edge compute or serverless runtimes (Cloudflare Workers, Lambda@Edge, Fastly), or the ability to ramp quickly
• You've led projects from scoping through shipping, not just contributed to them
• Good debugging instincts across service boundaries. You design systems so issues surface clearly rather than hiding
• Active use of AI-assisted development tools (Claude Code, Cursor, Codex, or similar) in your day-to-day workflow. You've used them to build and ship production features, not just experiment
• Willingness to work across unfamiliar parts of the stack