GTM AI Engineer

Headquarters: Americas Remote About Customer.io Over 9,000 companies — from scrappy startups to global brands — use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data. About the role Hi, my name is Nick Guardino, Senior Director of Marketing Ops at Customer.io , and I'm looking for a GTM AI Engineer to help take our AI agents from scrappy prototypes to production-grade systems our GTM teams can depend on. Over the last 3.5 months, our GTM AI team has built 11 agents now running in production, serving 120 active users and roughly 25,000 tool calls a day — all through custom CLIs that work, but weren't built to scale. We believe businesses can run leaner and go further when they deploy AI agents well, and we're figuring out that motion in real time. This role owns the scale and reliability layer so the rest of the team can keep building. What we value Craft over quick wins — energized by making things robust, not just making them work. A point of view — we want someone who asks "why did you build it that way?" and has a specific answer for what to do instead. Comfortable being wrong — you try things fast, and you course-correct just as fast. AI-native by default — you'd rather direct Claude to write and QA code than write it by hand. What you'll do Alpha-to-production ownership — take newly built agents from working v1 to production-ready: write evals, harden prompts and tool definitions, and refactor prototype scaffolding into clean, production-quality code. Observability & stability — instrument tracing, logging, and monitoring across the agent fleet so we catch regressions before our 120+ GTM users do. Deployment & infrastructure — stand up and maintain the pipelines that get agents into users' hands without surprises, owning environment parity and release hygiene on our GCP stack. Database administration — own how agents read from and write to our databases, safely and at scale. Fleet maintenance — monitor agent behavior in production, triage issues, and ship the steady stream of improvements that make an agent indispensable rather than just useful. Partner closely with the GTM AI team — free up our agent builders to stay in their zero-to-one wheelhouse while you own scale and reliability. Bring an outside point of view — tell us what we built wrong, and back it up with a plan to fix it. What we're looking for 4+ years in software engineering, platform/infrastructure engineering, or a similarly technical role, ideally at a B2B SaaS company. Comfort working in the terminal daily, with a real GitHub PR-and-deploy workflow. Cloud hosting experience — Kubernetes, VMs, or equivalent; Google Cloud experience strongly preferred. Experience with how agents interact with and edit databases, including some hands-on database administration. Familiarity with LLM-based application development: prompt engineering, tool/function calling, evals, and modern agent frameworks. Ability to prompt AI tools correctly, review their output critically, and direct them to QA their own work — this is an AI-native role, not a hand-coding one. Scrappy enough to iterate fast, disciplined enough to think about consistency once something needs to scale. A point of view, and the willingness to ask "why did you build it that way?" Compensation & Benefits We believe in transparency. Starting salary for this role is $140,000–$170,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. We know our people are what make us great, and we’re committed to taking great care of them.