Responsibilities
Customer-facing
- Lead the CX Strategy team, setting direction, developing team members, and aligning priorities to CX and company goals.
- Collaborate with CX leaders to drive performance metrics: resolution rate, CSAT, quality, resolution time, escalation rates, etc. Monitor the results and drive improvement when targets aren’t met.
- Own the CX AI roadmap from opportunity discovery through implementation — prioritize where AI can improve efficiency and customer experience, and sequence investments that compound over time.
- Collaborate with Systems and Engineering to drive CX AI performance — instruction set optimization, channel expansion (chat, voice, email), containment quality, and escalation handling, etc.
Internal AI tools & team productivity
- Define the standard for what an AI-augmented CX team looks like at Brex: how AI agents and human operators divide and conquer, where handoffs happen, and how to maintain customer experience quality as automation scales.
- Own the development and deployment of internal AI tools that make Brex’s CX team faster, more accurate, and more consistent — including agent-assist tooling, real-time guidance systems, QA automation, and workflow-level automations.
- Partner with Engineering, Data, and Product Ops to build and maintain the AI infrastructure underneath these tools — knowledge reliability, shared workflows, and feedback loops that improve both customer-facing and internal AI systems over time.
- Measure internal AI adoption and impact: track agent productivity, time-to-resolution improvements, QA automation rates, and coaching effectiveness. Close the loop between data and iteration.
Cross-functional & leadership
- Partner cross-functionally with CX Leadership, Strategy & Enablement, Product, Engineering, and Data to scope, build, and launch AI improvements. Represent CX in EPD conversations with a point of view grounded in customer outcomes and operational metrics.
- Drive internal AI adoption — ensure the CX team is equipped with the training, workflows, and confidence to work alongside AI effectively.
- Communicate AI performance and strategy to CX leadership and executive stakeholders; translate data into clear narratives that drive decisions.
Requirements
- 4+ years in CX strategy, AI operations, product operations, or a related function at the intersection of technology and customer experience — ideally in a fast-paced tech or fintech environment
- 1+ years managing or developing a team of 4+ ICs, with a track record of setting direction, developing people, and delivering results
- Proven experience owning and improving AI or automation initiatives in a support environment — from opportunity analysis through rollout and iteration, with measurable outcomes
- Product-minded builder: equally comfortable writing a requirements doc, configuring a platform, and partnering with Engineering to ship something net-new. You don’t wait for a product team to build what your customers need
- Strong analytical skills: comfortable digging into conversation data, contact driver analysis, and AI performance metrics to turn raw signal into smart decisions
- Technical fluency with AI-enabled CX platforms and the ability to ship directly or partner confidently with Engineering and Product to make automation work at scale
- Clear, direct communicator — you write with precision, translate between technical and non-technical audiences, and know how to make a data story land with leadership
- Proven cross-functional collaboration skills — you’ve worked across CX, Product, Engineering, and Data to drive customer-centric improvements
Bonus Points
- Hands-on experience with Sierra or comparable AI voice/chat/email platforms in a customer-facing environment
- Background in fintech, financial services, or enterprise SaaS
- Experience building or owning QA and eval frameworks for AI systems
- Experience building internal productivity tooling or agent-assist systems — whether through third-party configuration, prompt engineering, or partnering with Engineering to ship net-new tools
- Familiarity with product knowledge infrastructure — how content is structured, maintained, and surfaced to AI systems at scale
- Experience translating AI operational learnings into product feedback that influenced roadmap decisions
Compensation
The expected salary range for this role is $141,928 - $177,410. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.
BrexSeattle, WA
