AI Strategist

Blue Water Rail Services•Missoula, MT

About The Position

As a technical and strategic leader, the AI Lead will work closely with IT, Operations, Finance, Security, Legal, and Business stakeholders to ensure AI initiatives are secure, ethical, production-ready, and measurable. This role plays a critical part in shaping the company’s AI roadmap, supporting AI and Data Governance Working Groups, and enabling teams to leverage AI as a force multiplier across our organizations.

Requirements

Strong understanding of AI and machine learning concepts, including supervised/unsupervised learning, NLP, and LLM-based solutions.
Experience with cloud-based AI and data platforms (e.g., Azure, AWS, or equivalent enterprise environments).
Familiarity with AI/MLOps / model lifecycle management, including deployment, monitoring, and retraining.
Working knowledge of data architecture, integration patterns, and enterprise systems (ERP, PLM, operational systems).
Understanding of data governance, security, privacy, and responsible AI principles.
Ability to evaluate and guide the use of open-source and commercial AI tools.
Strong organizational skills with the ability to manage multiple tasks and priorities simultaneously.
Clear verbal and written communication skills for reporting and stakeholder engagement.
Ability to analyze project data, spot trends, and provide actionable insights.
High level of accuracy in tracking project progress, budgets, and timelines.
Ability to collaborate effectively with cross-functional teams and support project managers.
Basic problem-solving skills to assist with identifying and addressing project-level challenges.
Proficiency with project management and productivity tools (e.g., Microsoft Excel, PowerPoint, Smartsheet, or similar tools).
Bachelor’s degree in computer science, Engineering, Data Science, Applied Mathematics, or a related discipline.
5+ years of progressive experience in technology, data, analytics, or AI-related roles.
Demonstrated experience establishing or scaling an AI, analytics, or advanced data practice within a complex organization.
Experience delivering AI solutions in operations is highly desirable.
Proven track record of moving AI initiatives from concept to production with measurable business impact

Nice To Haves

Relevant certifications in AI, cloud platforms, or data engineering are considered an asset.

Responsibilities

Serve as a core member of the IT team contributing to governance, risk management, prioritization, and policy development.
Help develop and execute an enterprise AI strategy and roadmap, aligned with business priorities.
Act as the authoritative voice on AI capability, readiness, and feasibility across the organization.
Foster a collaborative, inclusive, and high-performing team culture with a strong emphasis on learning, experimentation, and accountability.
Define role profiles, skills development plans, and career pathways for AI practitioners.
Stay current on advancements in AI, Machine Learning, NLP, LLMs, GenAI, and cloud-based AI platforms.
Support the evaluation of emerging AI tools, frameworks, and vendors to ensure suitability for Washington Corporations security posture, and operations.
Lead the design and implementation of reusable AI architectures, pipelines, and components that can be leveraged across projects.
Support and Manage AI Platforms.
Partner with business leaders and technical teams to translate operational challenges into AI-enabled solutions.
Lead discovery and solution design efforts to ensure AI initiatives address real business problems and deliver measurable outcomes.
Oversee delivery of AI use cases that improve operational efficiency, decision-making, quality, safety, and program visibility.
Ensure AI initiatives move beyond proof-of-concept into production, with clear ownership, performance metrics, and lifecycle management.
Embed ethical AI principles, transparency, and risk mitigation practices into solution design and delivery.
Collaborate with Legal, Privacy, Security, and Data Governance teams to manage AI-related risks.
Support development of guidance for acceptable AI use, data handling, and model lifecycle management.
Act as a bridge between technical teams and business stakeholders, translating complex AI concepts into clear, actionable insights, promoting responsible adoption and practical value creation.
Support change management, training, and adoption efforts to build confidence and trust in AI solutions.
Contribute to executive-level updates, business cases, and decision materials related to AI initiatives.