Project & Program Management V

Astreya•Remote, TX, TX

6d•$132,240 - $208,800

About The Position

Our hyperscaler client's infrastructure organization is transforming how it plans, builds, and operates data center infrastructure — and AI is at the center of that transformation. We're looking for a Technical Program Manager to drive the highest-impact AI initiatives from concept through delivery, ensuring they scale across the organization and deliver measurable operational efficiency. This role sits at the intersection of AI/ML program delivery and infrastructure operations. You'll own the end-to-end program lifecycle for transformational AI initiatives — rallying cross-functional stakeholders, driving delivery milestones, and ensuring AI investments translate to real-world impact: fewer manual touchpoints, faster time-to-market, and the ability to scale without proportional increases in staffing.

Requirements

8+ years in technical program management or technical leadership roles driving complex, multi-team initiatives.
Program management rigor — Demonstrated ability to manage complex, multi-workstream programs: tracking deliverables across teams, holding stakeholders accountable, and driving decisions when ambiguity is high.
Tool / platform delivery track record — You've driven delivery of internal tools, platforms, or automation systems that other teams adopted. You understand what drives adoption — usability, operational readiness, and stakeholder buy-in.
AI/ML awareness — Working knowledge of how AI/ML solutions are integrated into operational workflows. You can engage meaningfully in discussions about data quality, model outputs, and automation boundaries without needing to be a practitioner.
Automation fluency — You understand automation design patterns and, critically, the safety considerations: where to place human-in-the-loop gates, how to validate outputs before they reach production, and when full autonomy is appropriate vs. risky.
Engineering partnership & technical acumen — You've worked embedded with engineering teams and can hold your own in technical discussions around APIs, data pipelines, system integrations, and deployment architectures. You don't write the code, but you understand the systems well enough to ask the right questions and unblock the right decisions.
Exceptional communication — Ability to synthesize complex technical programs into crisp leadership updates and drive alignment across senior stakeholders.

Nice To Haves

Experience leading AI/ML initiatives end-to-end — from problem framing and model development oversight through production deployment and iteration.
Product ownership experience — You've owned a product or platform end-to-end: defined requirements, prioritized backlogs, made trade-off decisions, and shipped iteratively based on user feedback.
Familiarity with data validation and cross-system consistency challenges (e.g., ensuring data alignment across multiple tools before production deployments).
Experience with infrastructure lifecycle programs — design, deployment, provisioning, or operations at scale.
Experience with phased rollout strategies — piloting at limited scope, defining promotion criteria, and scaling based on validation outcomes.
Exposure to capacity planning, resource orchestration, or supply/demand signal integration.
Understanding of MLOps concepts: model versioning, training pipelines, monitoring drift, and continuous improvement loops.
Background in field operations enablement — building tools or processes that support on-the-ground technicians (AR/IoT a plus).
Experience working as an embedded partner within a large technology organization, coordinating across both internal teams and external vendor/partner resources.

Responsibilities

Own strategic AI initiative delivery — Drive transformational AI programs from ideation through deployment, including milestone planning, dependency management, risk identification, and stakeholder alignment.
Translate vision into execution — Convert strategic AI goals into structured program plans with clear timelines, owners, success criteria, and go/no-go gates.
Drive accountability across cross-functional teams — Coordinate engineering, operations, and vendor partners; ensure deliverables ship on time and blockers are escalated quickly.
Advocate for end-user readiness — Ensure AI solutions account for adoption, usability, and operational readiness for field technicians, engineers, and operations teams.
Embed AI governance into delivery — Ensure all AI-driven workflows comply with AI guardrails, including validation frameworks, human-in-the-loop checkpoints, and rollback protocols.
Measure and communicate impact — Define KPIs (FTE avoidance, cycle time reduction, error rate improvement) and report outcomes to leadership with clarity.
Manage cross-initiative dependencies — Identify and actively manage shared resource constraints, inter-program dependencies, and external blockers that impact delivery timelines across a portfolio of concurrent initiatives.

Benefits

Medical provided through UHC (PPO, HSA, Surest options) / Medical provided through Kaiser (HMO option only) for California employees only
Dental provided through UHC
Nationwide Vision provided by UHC
Flexible Spending Account for Health & Dependent Care
Pre-Tax Account for Commuter Benefit/Parking & Transit (location-specific)
Continuing Education and Professional Development via various integrated platforms, e.g. Udemy and Coursera
Corporate Wellness Program provided by Goomi Group
Employee Assistance Program
Wellness Days
401k Plan
Basic and Supplemental Life Insurance
Short Term & Long Term Disability
Critical Illness, Critical Hospital, and Voluntary Accident Insurance
Tuition Reimbursement (available 6 months after start date, capped)
Paid Time Off (accrued and prorated, maximum of 120 hours annually)
Paid Holidays
Any other statutory leaves, paid time, or other ancillary benefits required under state and federal law