Director, Data & AI Product Management

Haag, a Salas O'Brien Company•,

11h•$215,000 - $245,000•Remote

About The Position

The Director, Data & AI Product Management will lead the portfolio of data and AI products built for Salas O'Brien's internal teams. This role will set product strategy, manage roadmaps and investment decisions, guide product owners, and ensure internal products deliver measurable adoption and business value. The goal of this role is to turn internal business needs into scalable data and AI products that are easy to adopt, clearly governed, and tied to measurable business value. The portfolio supports how the firm works every day, including enterprise data, project automation, pricing, business development, digital engineering operations, knowledge management, and talent-related solutions. This is a hands-on leadership role. You will manage product owners, set portfolio direction, participate in roadmap and backlog decisions, and stay close enough to the work to make informed tradeoffs on scope, timing, adoption, and value realization.

Requirements

Ten or more years of product management, product ownership, or related experience, including three or more years leading product managers or product owners.
Demonstrated experience delivering enterprise data, analytics, automation, or AI-enabled products for internal business users at scale.
Experience defining adoption metrics, value measures, and reporting methods that connect product usage to business outcomes.
Working knowledge of modern data platforms, lakehouse architecture, governed data environments, or related enterprise analytics capabilities.
Experience working with operational, financial, project, or enterprise resource planning data, including the data quality and reconciliation work needed to build trust.
Practical change management experience, including rollout planning, stakeholder enablement, training, feedback loops, and sustained adoption support.
Experience managing product investment decisions, budgets, vendor or platform costs, or funding recommendations for senior leaders.
Bachelor's degree in a technical, quantitative, business, or related discipline, or equivalent experience.
Strong written and verbal communication skills, including the ability to translate technical product decisions into business language.

Nice To Haves

Experience in environments with elevated governance, security, privacy, or regulatory expectations, including government contracting, healthcare, financial services, critical infrastructure, or other controlled-data settings.
Experience delivering applications on Databricks Apps or an equivalent embedded analytics or internal application surface.
Experience building or using a metric layer, semantic layer, or shared data model that multiple products consume.
Experience in a federated or multi-entity organization where adoption is earned through sponsorship, enablement, and demonstrated value.
Background as a practitioner in data engineering, analytics, business intelligence, product operations, or software delivery.

Responsibilities

Own the internal data and AI product portfolio, including strategy, roadmap, sequencing, investment priorities, and lifecycle decisions.
Lead and develop Data & AI Product Owners, setting clear expectations for product discovery, execution, adoption, value measurement, and stakeholder communication.
Lead the Data & AI Innovation and Ideas Committee by setting agendas, managing intake and prioritization, documenting decisions, and bringing funding requests or escalations to senior leadership with clear recommendations.
Convert approved ideas into delivery plans with named owners, timelines, success measures, adoption plans, and governance checkpoints.
Define and track adoption measures that reflect meaningful usage, including eligible-user activation, recurring active use, license utilization, and depth of use.
Own value realization by documenting hours saved, productivity improvements, revenue support, or cost avoidance using methods that Finance can validate.
Use product data, stakeholder feedback, and business outcomes to decide what scales, what needs improvement, and what should be retired.
Partner with leaders across Operating Groups to secure sponsorship, recruit early users, support rollout, and understand adoption barriers before assuming the solution.
Work closely with engineering, data platform, architecture, and security partners to ensure products are built on sustainable, governed, and scalable foundations.
Manage product-related budget considerations, including platform consumption, license spend, implementation effort, and cost per active user where applicable.
Partner early with governance, privacy, security, and client-facing stakeholders so product requirements are understood during design rather than after launch.