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.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 impactKey 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.