Head of Customer Deployment, Hazel AI

Hazel is building the AI engine for wealth management that helps unlock 10x growth, efficiency and value for financial advisors and their clients in a regulated industry. Since its launch last September, Hazel has organically and rapidly grown its user base.

Hazel is a part of Altruist's broader mission to make financial advice better, more affordable, and accessible to all.

This role is hybrid, with four in-office days per week at our San Francisco FiDi location.

We're looking for a senior post-sales leader to build and own Hazel's implementation and deployment function from the ground up. This person will define the methodology, operating model, team structure, and playbooks that enable wealth management firms to adopt Hazel quickly, successfully, and at scale.

This leader will own the most important implementation challenge in the business: turning complex, fragmented advisor data and workflows into a repeatable, scalable onboarding motion across a wide range of firms. They will partner closely with Sales, Product, and Engineering to improve time-to-value, shape self-service onboarding infrastructure, and turn customer deployment learnings into durable product and integration improvements.

- Build and own the post-sales function from zero, including methodology, team design, operating rhythms, metrics, and playbooks.

- Define and continuously improve a tiered deployment model, with distinct motions for middle-market firms and SMB customers, and clear time-to-value targets for each.

- Own the data migration and integration strategy at a systems level, solving implementation risk structurally rather than account by account.

- Build internal expertise and repeatable knowledge across the wealth management technology stack, including CRM, custodial, financial planning, and file storage integrations.

- Partner closely with Product to translate field learnings into product improvements, including integration templates, automated data ingestion, and self-service onboarding capabilities.

- Own core commercial post-sales outcomes across the book of business, including net revenue retention, gross revenue retention, time-to-value, and expansion revenue.

- Hire, lead, and develop a team of implementation individual contributors as the business scales.

- Partner with Sales on pre-sales demo environments and support the broader commercial motion where technical implementation credibility matters.

- Build self-service and Help Center infrastructure so lower-touch accounts can onboard successfully without requiring full white-glove deployment.

- 8-12 years of experience in post-sales leadership, implementation leadership, solutions engineering leadership, or a closely related function.

- Proven experience building a post-sales or implementation function from scratch, not just inheriting and managing an existing team.

- Deep technical credibility, with strong understanding of integration architecture, data pipelines, APIs, and implementation tooling.

- Demonstrated ability to lead implementation engineers and make sound build-versus-buy decisions across the post-sales tech stack.

- Strong commercial orientation, with a track record of thinking beyond customer satisfaction toward retention, expansion, and payback efficiency.

- Experience managing the tension between high-touch delivery and scalable execution, including productizing implementation work so team growth does not scale linearly with customer growth.

- Strong cross-functional leadership skills, with the ability to partner effectively across Sales, Product, and Customer-facing teams.

- Familiarity with RIA technology stack, including custodial data, CRM systems, financial planning tools, and related advisor workflows.

- Experience serving a market where reputation, implementation quality, and repeatability are critical differentiators.

This is a foundational hire; we expect to pay for proven capability. This role has a target compensation range of $200,000-$250,000 and competitive equity. Final level and compensation is individualized and will be determined based on overall experience, qualifications, and interview performance.