Technical Program Manager II, Infrastructure (Capacity & Efficiency)
Technology & IT
$103,965 - $214,044 USD yearly
- 2–4 years of program or project management experience (or equivalent), ideally touching infrastructure, platform, or cloud environments.
- Working knowledge of cloud platforms (AWS or similar) — compute, storage, and basic usage/cost concepts.
- Interest in, and some exposure to, capacity management and infrastructure efficiency (right-sizing, utilization, waste reduction); deep FinOps expertise is not required.
- Strong organizational and execution skills: able to track a program's moving pieces, follow up, and keep things on schedule.
- Clear written and verbal communication; comfortable presenting status and asks to engineering partners.
- Collaborative and coachable — works well with engineers and more senior TPMs, seeks input, and takes feedback well.
- Experience at a large-scale consumer tech or infrastructure organization is a plus.
- AI-first execution mindset: demonstrated ability to use GenAI to accelerate planning, program operations, and stakeholder communications—starting with AI drafts and applying strong judgment to validate, refine, and drive decisions.
- Workflow design, AI fluency, data & insights orientation: experience turning repeatable program work into durable, low-toil mechanisms and improving decision-making by using GenAI (e.g., strong prompting, vibe coding lightweight scripts/tools, dashboards, data analysis and leveraging agents where appropriate)
- Safety-by-design AI fluency: experience operating within AI governance expectations (risk assessment, data handling, model/output validation, auditability/traceability) and proactively identifying where AI use is not appropriate or requires additional controls.
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Preferred Qualifications
- Direct exposure to a FinOps, cost management, or capacity-focused function (nice-to-have, not required).
- Familiarity with dashboarding/BI tools (SuperSet, Tableau, Grafana, or similar).
- Basic SQL or scripting skills to pull and interpret usage data.
- Exposure to distributed systems, ML/AI infrastructure, or large-scale compute environments is a plus.
- Bachelor's degree in a relevant field such as Computer Science, or equivalent experience.