Applied AI Architect, GTM

About the role

Braze is building an Applied AI function for its GTM organization to help pioneer how modern revenue teams operate with AI. This role involves working at the forefront of AI-enabled GTM execution at a scaled global SaaS company.

Responsibilities

• Conduct stakeholder research across the GTM motion, from pre-sales through post-sales, to map out 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, and ensure the system gets better because the individuals building it never leave the commercial and customer motion.
• Own the reliability and quality of the systems you manage, monitor adoption, diagnose output failures, and tune/iterate continuously.
• 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, building reusable components and scalable frameworks.
• Partner with Growth Engineering, PMM, Solutions Consulting, Pricing, Customer Success, and leadership to ensure the systems you build are grounded in a cross-functional context and adopted by the people they serve.
• Help shape what this function becomes as the technology and the role category mature.

Requirements

• 6+ years of professional experience in a GTM role with direct involvement in the commercial motion: Solutions Consulting, Solutions Architecture, Account Executive, Sales Leader, GTM strategy, or a comparable role at a B2B SaaS company.
• Demonstrated, hands-on experience building AI-powered tools, agents, automations, or workflows that transformed real work processes, with concrete examples you can speak to in depth.
• Technical fluency sufficient to engage credibly on integration architecture, evaluate agent outputs at the system level, and contribute directly to prompt design, retrieval logic, and data workflows (e.g., Python, APIs, integrations) without always requiring translation from an engineering counterpart.
• A strong understanding of enterprise sales workflows, deal stages, and the daily operating reality of the GTM personas you will be building for: AEs, SCs, BDRs, sales leadership, CS, and business value teams.
• A track record of taking solutions from problem identification through field adoption, not just building and handing off.
• Comfort working across multiple workstreams simultaneously, balancing field engagement with system build and continuous refinement.
• Highly autonomous, self-directed, and comfortable operating as a senior individual contributor.

Qualifications

• Strong analytical capability sufficient to evaluate deal data, diagnose output failures, and build data-driven recommendation systems.
• Product Management background or experience, either as a career transition into GTM or as a complement to a field role, with demonstrated ability to ship things people actually use.
• Experience in Solutions Consulting, Solutions Engineering, or field architecture roles within enterprise SaaS.
• Familiarity with enterprise SaaS technology stacks (e.g., Salesforce, Gong, Slack, Snowflake).
• Experience building and scaling internal tools or systems that were adopted beyond your immediate team.
• Proficiency with AI development tools and platforms (e.g., Claude, Claude Code, Cursor, custom agent frameworks, API integrations, workflow automation tools).

Skills

• Highly autonomous, self-directed, and comfortable operating as a senior individual contributor.
• Strong analytical capability sufficient to evaluate deal data, diagnose output failures, and build data-driven recommendation systems.
• Experience in Solutions Consulting, Solutions Engineering, or field architecture roles within enterprise SaaS.
• Proficiency with AI development tools and platforms (e.g., Claude, Claude Code, Cursor, custom agent frameworks, API integrations, workflow automation tools).

Benefits

• Competitive compensation that may include equity.
• Retirement and Employee Stock Purchase Plans.
• Flexible 401(k) plan.
• Healthcare coverage.
• Flexible vacation policy.
• Comprehensive health and wellness programs.
• Professional development opportunities.
• Work-life balance initiatives.

Pay

The starting 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).

Schedule

This role offers a flexible schedule to support work-life harmony.