Technical Program Manager; AI

About Blackhawk Network

Today, through BHN’s single global platform, businesses of all kinds can tap into the world’s largest network of branded payment solutions. BHN helps businesses grow revenue, increase loyalty, motivate and reward their teams, disburse funds and engage consumers. Branded payment solutions include the issuance and distribution of gift cards, egifts, corporate payouts and rewards, along with the technology to deliver these products in seamless, integrated ways.

BHN’s network spans the globe with more than 400,000 consumer touchpoints. Learn more at

Hybrid flexibility:At Blackhawk Network, you’ll enjoy the best of both worlds—focused remote work plus in-person collaboration on
Tuesdays and Wednesdays,our regular in-office days at our Pleasanton headquarters. This rhythm gives you the tools, connection, and autonomy you need to make a real impact

At Blackhawk Network
, we’re shaping the future of global branded payments through cutting‑edge digital technologies that connect brands and people across the globe. Our fintech solutions — from digital payments and prepaid products to scalable infrastructure and security — drive innovation, customer loyalty, and business growth. At Blackhawk Network, we are accelerating the use of AI to improve how work gets done across the company while continuing to deliver innovative branded payment solutions at global scale.

We are seeking a Staff Technical Program Manager - AI to lead and scale cross‑functional AI programs that help business and technology teams automate work, improve operating efficiency, and deliver measurable outcomes. This role will sit at the intersection of business teams, AI architecture, AI engineering, data, operations, legal, compliance, and security to identify high‑value opportunities, shape roadmaps, and drive execution from concept through deployment.

This is first and foremost a program management role. The ideal candidate brings strong technical program management discipline, excellent cross‑functional leadership, and enough AI fluency to work with business leaders on initiatives that automate workflows, improve decision‑making, and increase productivity through AI and workflow automation capabilities.

• AI Program Intake and Prioritization

  • Partnering with business and technology stakeholders to evaluate requests, define scope, and sequence work against capacity and business value.
  • Translate business needs into clear program charters, milestones, and delivery plans for AI‑enabled automation initiatives.
  • Build and maintain the consolidated AI program roadmap for assigned business domains, including dependencies, delivery timelines, key decisions, and status across multiple concurrent initiatives.

  Program Governance and Execution

  • Lead end‑to‑end program execution for AI initiatives from planning through launch, ensuring strong governance, disciplined operating cadences, and predictable delivery.
  • Proactively manage risks, issues, cross‑team dependencies, escalations, and tradeoffs across engineering, data, architecture, and business teams.
  • Drive program reviews, decision forums, executive updates, and stakeholder communications to maintain alignment and remove blockers.
  • Ensure launch readiness by coordinating testing, rollout planning, operational handoffs, documentation, and post‑deployment follow‑up for AI solutions.
  • Partner closely with AI architects and technical teams to turn automation opportunities into executable programs, balancing business impact, technical feasibility, and delivery speed.
  • Support pilot execution and scaled rollout of AI capabilities, helping teams move from experimentation to repeatable operational use cases.
  • Define and track program KPIs such as throughput, productivity gains, cycle time reduction, quality improvements, adoption, and business value realization.
  • Establish repeatable program management templates, governance mechanisms, reporting structures, and playbooks to scale AI delivery across the organization.
  • Partner with analytics and operations teams to monitor results, identify improvement opportunities, and drive continuous optimization of AI programs after launch.