Applied AI Architect

At Braze, we have found our people. We’re a genuinely approachable, exceptionally kind, and intensely passionate crew.

We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity – inside and outside our organization.

To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success.

Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture.

If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can’t wait to meet you.

Braze is building an Applied AI function for its GTM organization to help pioneer how modern revenue teams operate with AI. This is a chance to work at the frontier of AI-enabled GTM execution at a scaled global SaaS company with sophisticated enterprise customers, advanced buyers, and a large customer-facing organization.

The team encodes the judgment of its best practitioners into systems that extend it across the entire revenue org, creates feedback loops that surface where execution can improve, and builds the AI-powered systems that make every GTM team member more effective at the moments that matter most.

This team is field-attached, product-minded, and outcome-driven. We treat GTM practitioners as users and their workflows as product surfaces. We build agents, intelligence layers, automations, and decision-support tools, then tune and refine them based on adoption, output quality, field feedback, and business impact. The goal is practical AI that earns trust in live GTM workflows and creates durable value at scale.

WHAT YOU’LL DO

As an Applied AI Architect, you will own a defined surface area across the revenue lifecycle and use AI to transform how Braze executes within it. You’ll operate across three modes simultaneously: as the practitioner whose field judgment (in part) the agents in your domain are modeled after, as the builder who designs and refines those agents on top of shared infrastructure, and as the observer who determines whether the outputs are actually changing how GTM teams engage with customers and prospects.

Your success is measured by whether practitioners adopt the outputs, whether those outputs improve behavior at critical moments, and whether that behavioral change produces measurable revenue and customer impact.

• Conduct stakeholder research across the GTM motion, from pre-sales through post-sales, to map where intelligence gaps, workflow friction, and handoff failures are most acute. Translate findings into a structured and prioritized backlog of problems to solve, including problem statements, impact, and feasibility scoring, dependencies, and stakeholders.
• Build and refine AI agents tailored to your area of the revenue lifecycle, contributing directly to system architecture, retrieval logic, and output calibration on top of shared infrastructure. Ship working solutions against real workflows
• Stay embedded in regional operating rhythms: pipeline reviews, deal cycles, QBRs, renewal planning, and account strategy sessions. The system gets better because the individuals building it never leave the commercial and customer motion. Field proximity is the operating discipline.
• Own the reliability and quality of the systems you manage. Monitor adoption, diagnose output failures, and tune/iterate continuously. You are not handing off to an ops team. You operate what you ship.
• Contribute to the shared knowledge hub by validating field signals, structuring deals and customer patterns, and ensuring that intelligence captured across the revenue lifecycle flows back in a form that produces better agent outputs.
• Recognize patterns across your area and scale what works. A system built for one account scenario, customer segment, or deal stage should become reusable infrastructure for adjacent situations.
• Partner with Growth Engineering, PMM, Solutions Consulting, Pricing, Customer Success, and leadership to ensure the systems you …