Applied AI Architect, GTM

Braze

Confirmed live today High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Chicago, ILNew York City, NY
Salary: $117,000–$175,000 / yr
Posted: 94 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $208k

This role $146k

$100k most similar roles pay here $274k

This role pays less than 89% of similar roles. Most pay $165,375–$250,071 — the shaded band above. At the midpoint, this role pays about $146k versus about $208k for comparable roles.

Based on 240 similar postings.

Employer

About Braze

Braze is a leading cloud-based customer engagement platform that enables brands to foster human connection with consumers through interactive, real-time, cross-channel marketing.

Braze currently has 108 open roles on FindRole.

Listed pay typically runs $149,000–$234,000 across 107 roles with salary data.

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At a glance

TL;DR · Applied AI Architect, GTM

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Applied AI Architect, GTM joins a specialized team building an Applied AI function to pioneer how modern revenue teams operate with artificial intelligence. This role focuses on creating AI-powered systems, agents, and decision-support tools that automate workflows and enhance the effectiveness of go-to-market practitioners. You will conduct stakeholder research across the revenue lifecycle, map friction points, and build tailored AI agents using shared infrastructure while ensuring high quality and reliability. The ideal candidate possesses deep experience in the revenue lifecycle, including roles like Solutions Consulting or Account Executive. Required skills include technical fluency in Python, APIs, and integration architecture, alongside proficiency with tools such as Claude, Cursor, and various automation platforms. You will solve complex problems by translating field judgment into scalable systems within a sophisticated enterprise SaaS environment to drive measurable business impact.

Skills

AI Python APIs Retrieval Logic Prompt Design Workflow Automation Claude Cursor Salesforce Gong Slack Snowflake Data Workflows System Architecture Integration Architecture SaaS

What you'll do

Conduct stakeholder research to identify and prioritize intelligence gaps and workflow friction across the GTM motion.
Build and refine AI agents tailored to specific areas of the revenue lifecycle using shared infrastructure.
Embed in regional operating rhythms like pipeline reviews and deal cycles to ensure systems remain relevant to field reality.
Own the reliability, quality, and continuous tuning of all managed AI systems and automated workflows.
Contribute to a shared knowledge hub by validating field signals and structuring common customer patterns.
Identify recurring patterns across segments or stages to create reusable infrastructure for broader organizational use.
Partner with cross-functional teams like Product Management and Engineering to ensure tools are adopted by the intended users.
Develop and document new playbooks for the Applied AI function as the technology and role category evolve.

What we're looking for

You must have at least 6 years of professional experience in a GTM role such as Solutions Consulting, Sales Leadership, or Account Executive.
You must have hands-on experience building AI-powered tools, agents, automations, or workflows that transformed real work processes.
You must possess technical fluency in Python, APIs, integrations, and prompt design to contribute to system architecture and data workflows.
You must have a strong understanding of enterprise sales workflows, deal stages, and the daily operating realities of GTM personas.
You must have experience in Solutions Consulting, Solutions Engineering, or field architecture roles within enterprise SaaS.
You should have a Product Management background or experience as a complement to your field role (preferred).
You should be proficient with AI development tools like Claude, Cursor, and various workflow automation platforms (preferred).
You should have familiarity with enterprise SaaS technology stacks including Salesforce, Gong, Slack, and Snowflake (preferred).

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