Forward Deployed AI Accelerator

Braze Customer Engagement Platform•Chicago, IL

1d•Hybrid

About The Position

Braze is building an internal AI Transformation function to change how every team at the company works. This team acts as practitioners, partnering directly with business units to make AI the default starting point for work. Forward Deployed AI Accelerators rotate across the company's non-revenue functions (Marketing, Finance, People, Legal, Operations, etc.), embedding with one function at a time to identify high-value workflows, rebuild them around AI with the people who own them, and ensure the teams can continue independently after the accelerator rotates out. This role is the broad-coverage, rotational counterpart to the Applied AI Architects, GTM team. The focus is on being product-minded and outcome-driven, treating users and their workflows as product surfaces, building on shared infrastructure, and tuning based on adoption, output quality, and business impact. The goal is to accelerate the impact of AI and scale it across Braze.

Requirements

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.
Experience running discovery or stakeholder research and translating it into a prioritized plan of work (problem statements, impact, feasibility assessment, 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 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 approach to different learners.
Comfort working across multiple workstreams and relationships simultaneously (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.

Nice To Haves

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.
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.

Responsibilities

Embed with a functional team or cross-functional cohort (approx. 15-25 people) to deeply learn their work and rebuild their highest-leverage workflows around AI alongside them.
Operate as a researcher to find where real friction and opportunity lie.
Operate as a builder to design and ship working agents on shared infrastructure.
Operate as a coach to move a team from initial AI contact to self-sufficiency.
Run enablement and discovery sessions across assigned functions (e.g., Marketing, Finance, People, Legal, Operations) to map intelligence gaps, manual effort, workflow friction, and handoff failures.
Translate findings into a structured, prioritized backlog of problems to solve, including problem statements, impact, feasibility scoring, dependencies, and stakeholders.
Create custom tools, agents, automations, and prompts tailored to high-value workflows, contributing to system architecture, retrieval logic, and output calibration on top of shared infrastructure.
Ship working solutions on real deliverables, not theoretical demos.
Move people through a progressive maturity model: from awareness to first win to regular AI integration to full workflow transformation to self-sufficiency.
Teach people to build and iterate on their own tools over time, aiming for independence.
Own quality during the engagement, monitor adoption, diagnose output failures, and tune continuously.
Transition load-bearing agents into the shared Platform layer so they run durably after rotation.
Recognize patterns and scale what works, making tools built for one team reusable for others.
Document every tool, playbook, and transformation pattern created.
Share wins visibly to create pull demand and celebrate successes.
Track individual and cohort progress against the maturity model.
Rotate to the next function when an engagement is complete (defined share of the cohort can build/modify their own tools, and load-bearing agents are productized).
Prepare cohorts for an agentic future, including designing, building, and overseeing autonomous multi-agent workflows.

Benefits

Competitive compensation that may include equity
Retirement and Employee Stock Purchase Plans
Flexible paid time off
Comprehensive benefit plans covering medical, dental, vision, life, and disability
Fertility benefits
Equal paid parental leave
Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
A curated in-office employee experience, designed to foster community, team connections, and innovation
Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
Employee Resource Groups that provide supportive communities within Braze
Collaborative, transparent, and fun culture recognized as a Great Place to Work®