Director, Product Management (Data & Agentic AI Platform)

Achieve•Tempe, AZ

7h•$220,000 - $250,000•Hybrid

About The Position

Achieve is seeking a Director of Product Management to own the strategy and launch of two foundational enterprise capabilities: a governed Data Platform and a shared Agentic AI Platform. The Data Platform will provide the governed data foundation and semantic layer for agentic workflows, natural-language analytics, standardized reporting, and enterprise data products. The Agentic AI Platform will provide shared infrastructure and a harness that enables teams across Achieve to build, launch, evaluate, and govern workflows and customer-facing agents. The role initially operates as a hands-on senior individual contributor, defining platform strategy and roadmaps, informing early technology and vendor choices, and working with engineering, data, security, risk, and compliance teams to launch and scale both platforms. As the platforms mature and become more embedded in the business, the role is expected to grow into a team leadership position. The work is intended to help Achieve replace static dashboards with trusted natural-language business insights, enable teams to create and govern AI-driven workflows, and establish risk-appropriate guardrails, trust, and auditability in a regulated industry. The role owns the enterprise data platform strategy, architecture, sequencing, migration, efficiency, and data-product roadmap. It also owns the semantic layer and business glossary, and defines how agents receive and maintain task-appropriate information, tools, instructions, and memory. For the Agentic AI Platform, the Director sets the vision and multi-year roadmap, develops reference workflows, enables use across operational and corporate teams, supports customer-facing and voice AI capabilities, and tracks emerging models, frameworks, and standards. The Director builds safety, evaluation, auditability, approvals, human checkpoints, rollback, access controls, and cost management into platform design. The role guides teams through operational change, reports progress and tradeoffs to senior executives, and partners with Data Engineering, InfoSec, and Compliance on governance, lineage, quality, privacy, and access controls. The position is hybrid in the Phoenix, AZ and San Francisco, CA metro areas, with 100% remote work available in other approved PST, MST, and CST locations.

Requirements

10+ years of product management experience owning platform, data, or infrastructure products, including services and APIs consumed by other teams.
Demonstrated platform mindset, with examples of shared infrastructure that delivered operating leverage rather than standalone point solutions.
Experience leading large data or platform migrations and managing cloud, storage, model, and vendor costs.
Knowledge of modern data architecture, including warehouses and lakehouses such as Snowflake and Databricks, ETL/ELT, event streaming, semantic layers, metric stores, and ontologies.
Experience building data governance into a platform, including lineage, quality, privacy, and access controls; experience in a regulated business such as financial services is relevant.
Working understanding of security, fraud, and regulatory risks specific to AI systems and sensitive financial data, and experience building controls for regulated businesses.
Comfort working with code, prompts, and evaluation frameworks, with sufficient depth to earn credibility with engineering teams.
Ability to connect platform work to business outcomes and demonstrate indirect value.
Proven ability to influence senior stakeholders, drive outcomes without direct authority, and explain technical concepts to executive audiences.
Demonstrated excellence in trusted, steady leadership, including composure during high-pressure pivots, transparent communication, fairness, and aligning stakeholders around shared goals.
Ability to set high-impact objectives, streamline cross-team execution, lead teams through change, and navigate ambiguity while providing clarity and flexibility.
Ability to drive performance through disciplined execution, clear accountability, dependable workflows, and scalable procedures.
Ability to identify talent, coach and develop people, hold managers accountable for development, and build leadership capability across teams.

Nice To Haves

Recent, demonstrated experience building agentic workflows for scaled operational use, including the ability to explain what was built, what failed, and what was changed.
Experience managing model, token, and inference costs for AI workloads.
Experience with customer-facing or voice AI, including authentication, latency, human handoff, and compliance.
Experience applying AI to the software development lifecycle.
Experience mentoring or leading product managers.

Responsibilities

Define and execute the enterprise data platform strategy, including target architecture, sequencing, and success metrics.
Lead migration of existing data, ETL processes, and dashboards while minimizing business disruption.
Optimize replication, storage, and compute to reduce inefficiencies and costs.
Own the roadmap for enterprise data products and services across identity, consent, product interaction, and insights.
Enable agentic and natural-language analytics so business users can self-serve trusted insights.
Own the enterprise semantic layer and business glossary, establishing governed definitions for BI users and agents.
Define how agents receive task-appropriate information, tools, instructions, and memory, and how context is assembled, versioned, tested, and kept current.
Set standards for measuring context quality, including retrieval accuracy, grounding, freshness, and cost.
Define access models that restrict agents to information permitted for each user and task.
Set the vision and multi-year roadmap for the enterprise agent harness used to build, orchestrate, evaluate, and monitor agents.
Build reference workflows that demonstrate the agent harness and provide models for other teams.
Enable teams across operations, servicing, sales, and corporate functions to build and run workflows on the platform, prioritized by value and feasibility.
Enable customer-facing AI experiences and voice agents, including authentication, latency, human handoff, and compliance capabilities.
Support AI-driven software development lifecycle capabilities to improve engineering throughput and quality.
Track AI models, agent frameworks, and emerging standards and translate relevant developments into platform decisions.
Build platform safety capabilities, including evaluation, audit trails, approval thresholds, human-in-the-loop checkpoints, and rollback, matched to risk; assess where AI should not be used.
Guide teams in changing how they operate and report AI transformation progress and tradeoffs to senior executives.
Make infrastructure, token, and inference costs visible and manageable, and manage vendor and model spending as part of the roadmap.
Partner with Data Engineering, InfoSec, and Compliance to build governance, lineage, quality, privacy, and access controls into platform design.
Influence senior stakeholders and drive outcomes without direct authority; explain technical concepts to executive audiences.
As the platforms mature, the role is expected to grow into a team leadership position.

Benefits

401(k) with employer match.
Medical, dental, and vision coverage, with HSA and FSA options.
Competitive vacation and sick time off.
Dedicated volunteer days.
Wellness support through an Employee Assistance Program and Talkspace, and fitness discounts.
Up to $5,250 reimbursement for eligible education expenses.
Pet care discounts.
Financial support in times of hardship through the Achieve Care Fund.
Employee resource groups and a commitment to diversity and inclusion.
Bonus and benefits in addition to salary.