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.

• 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.

• 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.

• 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…