Artificial Intelligence (AI) Ops Specialist

ST Engineering North America•Baltimore, MD

3d•$65,000 - $93,000

About The Position

The AI Ops Specialist will operationalize how the MRAS AI team works day to day. The role implements corporate AI policies and procedures, including governance and execution frameworks, and designs compliance-by-design ways of working. It defines and helps build tools to scope, track, and monitor AI projects throughout their lifecycle, embedding policy checks and required attestations directly into those tools. The Specialist leads the AI training program by influencing curriculum, authoring and curating materials, engaging third-party trainers as needed, and tracking and rewarding completion to upskill employees. The role also implements AI capabilities and features within operational tools so the AI team models an AI-native approach to work. It is suited to an early-career professional or intern-to-hire candidate with demonstrable impact and a drive to build operational excellence in AI. At ST Engineering MRAS, employees work on advanced technologies and systems supporting customers worldwide. The company produces and assembles complex aerostructures, including aircraft and rocket components, engine nacelle systems, thrust reversers, and advanced composite products. It applies digital technologies and automation in composite design and manufacturing, and is expanding its maintenance, repair, and overhaul capabilities. The role works across Engineering, Quality, Operations, Programs, Legal, IT/Cyber, and CI, and coordinates with corporate AI, Risk & Assurance, and Digital Platform teams as required. Employment is contingent on satisfactory background check and drug screening results. The position involves access to export-controlled technology, requiring U.S. Person status or a legally recognized export control exception or authorization, with valid proof required if hired.

Requirements

Bachelor’s degree (BS) in a relevant field.
At least 1 year of demonstrated experience building or operating digital workflows and tools, which may be through an internship, co-op, project, or entry-level role.
U.S. Person status or a legally recognized export control exception or authorization is required for access to export-controlled technology; valid proof must be provided if hired.
Successful completion of a background check and drug screening is a condition of employment.

Nice To Haves

Experience implementing operational tooling with Microsoft technologies such as SharePoint/Lists, Power Automate, Power BI, or Copilot Studio is highly preferred.
Exposure to governance frameworks and control checklists, with the ability to embed approvals and attestations into tooling.
Interest in continuous improvement, such as Lean or Six Sigma training.
Passion for teaching and enablement; experience creating learning content or delivering workshops.
Familiarity with AI concepts and agentic workflows, including LLMs, prompt design, Copilot/Studio, or Azure OpenAI, and eagerness to learn deeply.
Strong process orientation and ability to translate policy and governance requirements into practical templates, checklists, and workflows.
Clear communication skills with stakeholders across business, engineering, legal, IT, and CI; organized and detail-oriented.
Curiosity and bias to action; comfort owning outcomes and iterating in a fast-moving environment.
Practical experience with agentic solutions or AI assistants for workflows.

Responsibilities

Operationalize corporate AI policy and governance by embedding MRAS and ST Engineering requirements and execution playbooks into daily operations and project tooling.
Define and help implement tools and workflows for AI project intake, scoping, approvals, tracking, and reporting, integrating guardrails, attestations, and audit trails by default.
Lead the AI training program by creating curricula and materials, scheduling and running training, engaging third-party trainers, and tracking completions and recognition.
Implement AI features, including assistants, agents, and orchestration, within operational tools.
Define operational KPIs for training, project throughput, compliance status, cycle time, and realized value, and prepare monthly leadership readouts aligned with AI Steering Committee and enterprise reporting processes.
Collaborate with Engineering, Quality, Operations, Programs, Legal, IT/Cyber, and CI to align policies, approvals, and data readiness checklists; coordinate with corporate AI, Risk & Assurance, and Digital Platform teams as required.
Capture feedback and continuously improve processes to increase speed, quality, and compliance in AI delivery at MRAS.