AI Solutions Architect / Program Manager, Cross-Domain

AST SpaceMobile • Lanham, MD

2d

About The Position

AST SpaceMobile is building the first and only global cellular broadband network in space to operate directly with standard, unmodified mobile devices based on our extensive IP and patent portfolio and designed for both commercial and government applications. Our engineers and space scientists are on a mission to eliminate the connectivity gaps faced by today’s five billion mobile subscribers and finally bring broadband to the billions who remain unconnected.
Position Overview
We are seeking an AI Solutions Architect / Program Manager to serve as a senior technical and organizational leader within a rapidly scaling AI and autonomy organization. This hybrid role blends AI/ML systems architecture expertise with technical program management, ensuring complex AI initiatives are delivered as an integrated, coherent platform rather than isolated solutions.
In this role, you will define end‑to‑end AI system architectures across multiple domains, design scalable machine learning pipelines for image‑ and video‑based workloads and manage cross‑functional programs to deliver results on schedule, within scope, and aligned to strategic priorities.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Systems Engineering, or a related field
• A minimum of 8 years of combined experience in AI/ML solutions architecture and technical program management
• At least 3 years of hands‑on experience in each discipline
• Strong interpersonal and collaboration skills across technical and non‑technical teams
• Proven ability to communicate complex technical concepts to executive stakeholders
• Excellent written and verbal communication skills
• Strong organizational skills with meticulous attention to detail
• Ability to balance strategic architecture thinking with practical execution
• Comfort operating in fast‑paced, ambiguous environments
• AI/ML frameworks and tooling (e.g., ML training, experiment tracking, model deployment)
• Distributed training and GPU‑accelerated compute environments
• Cloud and hybrid infrastructure (e.g., containerization, orchestration platforms)
• Data pipelines and large‑scale storage systems
• Program and project management tools supporting agile delivery
• Ability to work in a standard office or remote environment
• Ability to use a computer and related equipment for extended periods
• Ability to participate in meetings, reviews, and collaborative sessions

Nice To Haves

• Master’s degree or equivalent advanced experience preferred
• Experience architecting ML pipelines for video understanding, computer vision, or multimodal AI systems
• Background delivering AI initiatives from research through production deployment
• Experience supporting complex, multi‑team or multi‑site technical programs
• Familiarity with scaled agile frameworks and enterprise delivery models
• Exposure to regulated, safety‑critical, or defense‑adjacent environments
• Relevant certifications (e.g., PMP, PMI‑ACP, TOGAF, or equivalent)

Responsibilities

• Define and maintain end‑to‑end AI system architectures, ensuring shared data models, integration standards, and API patterns across workstreams
• Architect scalable ML training pipelines for image‑ and video‑based models, including data ingestion, annotation workflows, distributed training, validation, and deployment
• Design infrastructure architectures to support large‑scale video ML workloads, including data storage, preprocessing pipelines, and GPU‑based training environments
• Define and oversee MLOps practices across model lifecycles, including experiment tracking, model versioning, automated retraining, deployment strategies, and performance monitoring
• Manage the master program schedule across multiple teams, tracking milestones, dependencies, risks, and delivery timelines
• Lead technical reviews and make informed build‑vs‑buy decisions for AI platforms, tooling, and infrastructure
• Coordinate integration points to ensure alignment across teams and avoid duplication of effort
• Track deliverables against defined milestones and provide regular, executive-level progress reporting
• Manage budget tracking, resource planning, and procurement activities related to AI infrastructure and tooling
• Define and document data flow architectures and interface contracts between systems and teams
• Facilitate cross‑functional collaboration with engineering, operations, manufacturing, and product stakeholders
• Lead planning cycles, sprint ceremonies, and retrospectives in a research‑to‑production environment
• Evaluate emerging AI technologies and recommend adoption strategies aligned to organizational goals

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1-10 employees