AI Strategist

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. 
 

Key Accountabilities
AI Strategy & Practice Leadership
•    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.
 

Team Leadership & Capability Development
•    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.
 

Technology Support
•    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.
 

Business Engagement & Value Delivery
•    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.
 

Governance, Risk & Responsible AI
•    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.
 

Communication & Change Enablement
•    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.
 

Technical Skills & Knowledge
•    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.

Skills and Competencies Required: 
•    Organization: Strong organizational skills with the ability to manage multiple tasks and priorities                     simultaneously.
•    Communication: Clear verbal and written communication skills for reporting and stakeholder engagement.
•    Analytical Thinking: Ability to analyze project data, spot trends, and provide actionable insights.
•    Attention to Detail: High level of accuracy in tracking project progress, budgets, and timelines.
•    Teamwork: Ability to collaborate effectively with cross-functional teams and support project managers.
•    Problem Solving: Basic problem-solving skills to assist with identifying and addressing project-level challenges.
•    Tech-Savvy: Proficiency with project management and productivity tools (e.g., Microsoft Excel, PowerPoint, Smartsheet, or similar tools).

Education:
•    Bachelor’s degree in computer science, Engineering, Data Science, Applied Mathematics, or a related discipline.
•    Relevant certifications in AI, cloud platforms, or data engineering are considered an asset.
 

Experience:
•    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