Sr. Staff Technical Program Manager - Ads

Shopify

About The Position

Shopify Technical Program Managers lead large-scale technical programs that build products for merchants, enable entrepreneurship, and create business impact. The Sr. Staff Technical Program Manager supporting Ads partners with Engineering, Product, Data Science, and business stakeholders to build and scale advertising technology connecting merchants, advertisers, and audiences. The role shapes and delivers platform capabilities that support relevant advertising experiences, improve campaign performance, and drive sustainable growth while protecting the customer experience. The role requires technical judgment and the ability to connect platform architecture and product strategy to business outcomes. The TPM guides teams through ambiguity, trade-offs, risks, and interdependencies, translating complex initiatives into actionable plans. Programs may span the advertising lifecycle, including ad delivery and serving, targeting and personalization, campaign management, measurement and attribution, experimentation, data and ML infrastructure, monetization, and platform reliability. The TPM also helps establish technical foundations and operating mechanisms for scaling advertising capabilities efficiently and responsibly. This position owns complex, cross-functional programs from problem definition and technical discovery through planning, implementation, launch, adoption, and ongoing optimization. It connects technical delivery to measurable outcomes, builds alignment across organizational boundaries, improves operational execution, uses AI tools thoughtfully, and communicates program health and business impact to technical and executive audiences.

Requirements

Extensive experience in technical program management, software engineering, technical product management, or a related technical discipline, with a proven track record of delivering complex programs involving multiple engineering teams.
Demonstrated ability to drive large, cross-organizational initiatives from strategy and problem definition through technical execution, launch, and measurable outcomes.
Strong technical judgment and ability to engage meaningfully in architecture and design discussions involving distributed systems, APIs, data platforms, or other complex software systems.
Experience translating business objectives into technical roadmaps, program plans, measurable success criteria, and prioritized execution across interdependent teams.
Ability to use data and analytical reasoning to evaluate trade-offs, assess program performance, identify risks, and guide decisions.
Ability to influence without authority, build stakeholder alignment, navigate competing priorities, and drive decisions through ambiguity.
Strong written and verbal communication skills, including explaining complex technical concepts and communicating status, risks, and recommendations to technical and executive audiences.
Experience building program management mechanisms for dependency and risk management, milestone tracking, launch readiness, executive reporting, and continuous improvement.
Proactive and resourceful problem-solving approach, with a bias toward action, accountability, and meaningful results.
Familiarity with AI-powered tools and coding assistants such as Cursor, Claude, ChatGPT, or Perplexity, and ability to apply them thoughtfully to technical problem-solving and program execution.

Nice To Haves

Experience in digital advertising, advertising technology, ad platforms, commerce media, marketplace monetization, or performance marketing.
Familiarity with advertising lifecycle areas such as ad serving, targeting and personalization, campaign management, auction and bidding systems, measurement and attribution, experimentation, or revenue optimization.
Experience working with Data Science, Machine Learning, or Analytics teams to deliver data-driven products, experimentation platforms, optimization systems, or ML-powered capabilities.
Experience operating large-scale, revenue-critical platforms where reliability, latency, scalability, data quality, and customer experience are important.
Experience defining and tracking business and technical metrics such as incremental revenue, adoption, advertiser performance, conversion, experimentation outcomes, service reliability, or operational efficiency.
Experience leading platform migrations, system modernization, partner integrations, or multi-team initiatives with complex technical dependencies.
Experience using AI-assisted development, data analysis, automation, or rapid prototyping to improve execution speed and decision quality.

Responsibilities

Own complex, cross-functional programs from problem definition and technical discovery through planning, implementation, launch, adoption, and ongoing optimization.
Establish program goals, milestones, dependencies, owners, and success criteria.
Translate strategic priorities into executable roadmaps and measurable outcomes, balancing merchant and advertiser value, revenue opportunity, customer experience, engineering investment, and time to market.
Work with engineering leaders to understand system architecture, APIs, data flows, distributed services, and technical constraints; help evaluate options, surface trade-offs, resolve dependencies, and inform decisions.
Drive programs across advertising platform capabilities, including ad serving and delivery, targeting and personalization, campaign and budget management, auction and optimization systems, measurement and attribution, experimentation, and advertising data infrastructure.
Partner with Data Science, Analytics, and Engineering to define success metrics, establish instrumentation and reporting, evaluate experiments, identify performance gaps, and turn insights into decisions.
Connect technical progress to outcomes such as incremental revenue, advertiser performance, adoption, reliability, and customer experience.
Align Engineering, Product, Data Science, Infrastructure, and business teams; surface competing priorities, drive decisions, resolve blockers, and establish shared accountability.
Establish effective program mechanisms that improve visibility, decision-making, launch readiness, risk management, and execution predictability.
Identify recurring bottlenecks and reduce operational toil through improved systems, automation, and repeatable practices.
Use AI tools and coding assistants to accelerate technical discovery, analyze information, prototype solutions, automate workflows, synthesize program signals, and identify emerging risks; validate outputs and account for privacy, security, and responsible AI requirements.
Communicate program health, technical risks, decisions, trade-offs, and business impact to engineers, cross-functional partners, and executive leadership.