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AI / ML

GTM AI Engineer

Customer.io · LATAM, Canada, United States · full-time · Remote

AI / MLfull-timeRemoteLATAM, Canada, United StatesUSD 140,000 – 170,000 / yearly
Software EngineeringDirector
RemoteJobs editorial overview

Strategic Overview

GTM AI Engineer at Customer.io is a aiml opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.

The published role emphasizes work such as 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…

The role is listed for LATAM, Canada, United States with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Software Engineering, Director.

Job seeker snapshot

Key information at a glance

Role focusAI / ML
LocationLATAM, Canada, United States
WorkplaceRemote
Employmentfull-time
Experience4+ years
SalaryUSD 140,000 – 170,000 / yearly
PostedOct 27, 2026
Last seenOct 27, 2026
Role context

About This Role

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.

What the role delivers

Key Responsibilities & Objectives

  • 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.
Candidate blueprint

Required Qualifications & Candidate Blueprint

  • 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.
Compensation & benefits

Salary & Benefits

Published compensation: USD 140,000 – 170,000 / yearly

Live market comparison

Salary Benchmark

This role’s published compensation is compared with current employer-disclosed salary ranges for the same role in the same currency.

This jobUSD 140,000 – 170,000 / yearly
Current market range$107,360 – $555,000
Comparable jobs63

Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.

Employer-provided source content

Full Job Description

The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.

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. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build.

We know our people are what make us great, and we’re committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family. We also offer 16 weeks paid parental leave, unlimited PTO, stipends for remote work and wellness, a professional development budget, and more.

See full benefits here →

Our Process

No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision.

  1. 30-minute Zoom call with Recruiter
  2. 45-minute Zoom call with Hiring Manager
  3. 45-minute Zoom call with a member of the GTM AI team
  4. 60-minute Live technical session with the team

All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process.

Customer.io recognizes the stifling impact of systemic injustice on diverse communities. We commit to using our influence to increase inclusion and equity within the tech industry. We strive to build an inclusive team culture, implement bias-free hiring practices, and develop community partnerships to expand our global impact.

Zoom is the only video conference platform that we use, virtual interviews will be conducted using the video capability (i.e., not via the chat), and offers will be extended in writing on official Customer.io letterhead. Please be vigilant in all of your job search activity, and if you have any questions please contact jobs@customer.io.

Join us!

Check out our careers page for more information about why you should come work with us! We believe in empathy, transparency, responsibility, and, yes, a little awkwardness. If you’re excited by what you read — apply now.

RemoteJobs original analysis

Editor’s Market Perspective (Our Custom Analysis)

Why This Position Matters

This aiml opening is a useful opportunity for candidates whose experience matches Software Engineering, Director. Its strongest career signal is the scope of the work itself — particularly 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. — rather than a generic title alone.

Resume & Application Strategy

For the application, mirror the employer's language where it truthfully matches your background: foreground Software Engineering, Director, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.

Source transparencyjobicy

We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.