Forward Deployed AI Accelerator

Braze is building an internal AI Transformation function to change how every team at the company works. Not as a center of excellence that publishes best practices from a distance, but as a team of practitioners partnering directly with business units to make AI the default starting point for work.

Within that team, Forward Deployed AI Accelerators rotate across the company's non-revenue functions — Marketing, Finance, People, Legal, Operations, and beyond — embedding with one function at a time to find the highest-value workflows, rebuild them around AI alongside the people who own them, and leave each team able to keep going without us. A sibling team, Applied AI Architects, GTM, applies the same craft permanently attached to specific stages of the revenue lifecycle; this role is the broad-coverage, rotational counterpart.

We are product-minded and outcome-driven. We treat the people we serve as users and their workflows as product surfaces, we build on shared infrastructure, and we tune what we ship based on adoption, output quality, and business impact. Braze employees are already building agents that compress multi-day workflows into minutes and tools that transform processes like research, reporting, and operational escalations. This team exists to accelerate that impact and systematically scale it across Braze.

As an Applied AI Architect, Core Business, you'll embed with a functional team or cross-functional cohort of approximately 15–25 people, learn their work deeply, and rebuild their highest-leverage workflows around AI alongside them. You'll operate across three modes: as the researcher who finds where the real friction and opportunity live, as the builder who designs and ships working agents on shared infrastructure, and as the coach who moves a team from its first contact with AI to self-sufficiency — and then rotates to the next function.

Unlike your GTM counterparts, you are not permanently attached to one area. Your measure of success is durable business impact aligned to key financial and efficiency goals, adoption that persists after you rotate out, and cohorts that can build for themselves.

• →Run enablement and discovery across your assigned functions. Lead enablement sessions and stakeholder research across the teams you cover (e.g., Marketing, Finance, People, Legal, Operations) to map where intelligence gaps, manual effort, workflow friction, and handoff failures are most acute. Translate findings into a structured, prioritized backlog of problems to solve — problem statements, impact, and feasibility scoring, dependencies, and stakeholders — and use it to decide where to dig in and rebuild the process first.
• →Build alongside the team. Create custom tools, agents, automations, and prompts tailored to the highest-value workflows, contributing directly to system architecture, retrieval logic, and output calibration on top of shared infrastructure. Ship working solutions on real deliverables, not theoretical demos.
• →Coach toward self-sufficiency. Move people through a progressive maturity model: from awareness to first win to regular AI integration to full workflow transformation to self-sufficiency. Meet people where they are, and teach them to build and iterate on their own tools over time. The goal is independence, not dependence on you.
• →Own quality during the engagement, then hand up the durable pieces. Monitor adoption, diagnose output failures, and tune continuously while you're embedded. As the engagement matures, transition the cohort's load-bearing agents into the shared Platform layer so they run durably after you rotate out — you operate what you ship until it's productized, not before.
• →Recognize patterns and scale what works. A tool built for one team should become reusable infrastructure for the next. Document every tool, playbook, and transformation pattern you create so the full team can compound each other's work.
• →Build momentum. Share wins visibly within your cohort and with leadership to create pull demand and celebrate what's working. Track individual and cohort progress against the maturity model.
• →Know when to rotate. An engagement is complete when a defined share of the cohort can build and modify their own tools, and their load-bearing agents have been productized into the Platform layer. Then you move to the next function.
• →Prepare cohorts for an agentic future. Not just prompt writing, but designing, building, and overseeing autonomous multi-agent workflows that handle real business processes.

We're looking for people who have already lived the transformation they'll be driving for others. You've used AI to fundamentally change how you work, and you can show your work.

• You are a builder and a deep AI practitioner. You build agents, automations, and tools fluently. You don't just know what AI can do in theory; you've built things that changed how real work gets done, and you can build in real time alongside the people you support. You can scope and prioritize solutions, contribute to system architecture and retrieval design, evaluate outputs for quality, and diagnose why something was missed at the system level rather than just the content level.
• You are a researcher and systems thinker. You can walk into a function you don't know, run the interviews and sessions that surface where the real friction is, and turn what you hear into a prioritized, defensible backlog. When you build something that works for one person or team, you immediately see how it applies to ten others, and you think in reusable components and scalable playbooks.
• You are an exceptional coach and communicator. You can meet people wherever they are, from skeptical to enthusiastic. You create desire for progress and adapt your approach to each person. You know that adoption is a human problem, not a technology problem.
• You think like a product leader. When you identify a gap, you scope the problem, define the user, map the workflow, and build the solution. You treat the people you serve as your users and their workflows as your product surface, and you know the difference between shipping something and shipping something people actually use.
• You understand how business functions run. You've worked in or closely with the kinds of teams you'll be embedded in (marketing, finance, people, legal, operations). You know that understanding someone's work is a prerequisite to transforming it.
• You are biased toward action and speed. You'd rather show someone a working proof of concept on their actual deliverable today than present a polished deck on what's theoretically possible next quarter.
• You are comfortable with ambiguity. This is a new team building a new operating model at Braze. The playbook will be rewritten as we learn, and you thrive in that environment.
• 5+ years of professional experience in a role requiring analytical thinking, problem-solving, and cross-functional collaboration
• Demonstrated, hands-on experience building AI-powered tools, agents, automations, or workflows that transformed real work processes (not just using AI as a chatbot), with concrete examples you can speak to in depth
• Experience running discovery or stakeholder research and translating it into a prioritized plan of work — problem statements, impact, and feasibility assessment, and clear next steps
• Technical fluency sufficient to engage credibly on integration architecture, evaluate agent outputs at the system level, and contribute to prompt design, retrieval logic, and data workflows (e.g., Python, APIs, integrations) without always requiring translation from an engineering counterpart
• Track record of coaching, teaching, or enabling others, with evidence that people you've worked with actually changed how they work
• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences and adapt your approach to different learners
• Comfort working across multiple workstreams and relationships simultaneously (you'll be supporting 15–25 people at varying stages of their AI journey)
• Product Management background or experience, with demonstrated ability to ship things people actually use
• Experience in marketing, finance, people/HR, legal, operations, or a closely adjacent business function
• Proficiency with AI development tools and platforms (e.g., Claude, Claude Code, Cursor, custom agent frameworks, API integrations, workflow automation tools)
• Experience with change management, organizational transformation, or large-scale enablement programs
• Familiarity with enterprise SaaS technology and data stacks (e.g., Salesforce, Slack, and Snowflake)
• Experience building and scaling internal tools, templates, or playbooks that were adopted beyond your immediate team
• Background in consulting, solutions engineering, technical program management, or other roles that combine technical depth with business context

AI is transforming how every company operates. Most companies respond by buying tools and hoping adoption follows. Braze is taking a different approach: embedding practitioners directly with teams to build the muscle memory of AI-first work from the inside out.

Doing that well across the business requires a rare intersection. An engineer without a business context builds a technically correct tool that the team ignores. A functional expert without build capability produces insight that doesn't scale. The person who is both — and who can coach a team to keep going after they leave — is exactly who this role is for. You'll move across the company, find the work that matters most, rebuild it alongside the people who own it, and leave each team more capable than you found it.

If you've already transformed your own work with AI and want to do it for an entire company, this is the role.

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $123,000 and $184,000/year, with an expected On Target Earnings (OTE) between $145,000 and $217,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

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