AI Strategy & Enablement Lead

AI Strategy & Enablement Lead 

Role Summary

The AI Strategy & Enablement Lead leads cross-functional coordination of AI initiatives, ensuring that AI efforts across teams are aligned, visible, prioritized, and connected to business and technical outcomes.

This role acts as an internal AI strategist, evangelist, and operating-system builder for AI adoption across the company. While technical AI leads own execution within specific domains, this role ensures the broader AI portfolio is coherent, well-governed, communicated, and supported across teams.

Key Responsibilities

• Define and maintain the company-wide AI strategy, including priority domains, investment themes, adoption principles, and measurable outcomes.
• Coordinate AI initiatives across quantum systems, software, hardware, operations, product, data, IT, and business teams to avoid duplication and surface shared opportunities.
• Partner with technical leaders to align domain-specific roadmaps with the broader company AI strategy.
• Identify high-value internal AI use cases across engineering, operations, research, customer workflows, documentation, productivity, and decision support.
• Establish an AI portfolio management process, including initiative intake, prioritization, ownership, progress tracking, risk review, and executive reporting.
• Drive internal AI education, enablement, and evangelism through workshops, demos, playbooks, office hours, and success-story sharing.
• Help define company-wide AI principles around responsible use, human oversight, data sensitivity, model selection, security, validation, and operational trust.
• Build alignment between experimental AI pilots and scalable deployment paths, ensuring promising efforts have owners, resourcing, governance, and adoption plans.
• Maintain visibility into external AI trends, tools, vendor capabilities, and competitive developments relevant to the company’s technical and operational strategy.
• Translate AI opportunities into clear narratives for executives, technical teams, and operators, helping the organization understand where AI should be used and where it should not.

Required Background

• Strong experience in AI strategy, technical program leadership, product strategy, innovation, digital transformation, or emerging-technology adoption.
• Ability to work credibly across technical and non-technical teams, including engineering, research, operations, product, security, and leadership.
• Strong understanding of modern AI capabilities, limitations, adoption patterns, and organizational change management.
• Experience coordinating cross-functional initiatives with multiple stakeholders, ambiguous ownership, and evolving requirements.
• Excellent communication skills, with the ability to turn technical AI concepts into practical priorities, operating models, and executive-ready narratives.
• Strong systems thinking: understands how AI initiatives interact across teams, tools, data flows, governance, and business goals.

Preferred Background

• Experience introducing AI tools or platforms inside a technical organization.
• Familiarity with ML lifecycle concepts, model evaluation, data governance, AI risk management, or responsible AI practices.
• Experience in deep tech, quantum computing, robotics, scientific instrumentation, advanced manufacturing, or complex engineering environments.
• Background in technical product management, strategy, consulting, developer relations, or internal platform enablement.
• Experience building communities of practice, internal enablement programs, or cross-functional technology councils.

Success Measures

• Company-wide AI strategy established with clear priorities, owners, decision forums, and communication channels.
• AI initiatives across teams are visible, coordinated, and mapped to measurable outcomes.
• Reduced duplication of AI efforts and improved reuse of tools, data patterns, vendors, and lessons learned.
• Increased adoption of approved AI tools and practices across technical and operational teams.
• Regular AI demos, workshops, portfolio reviews, and executive updates create shared understanding and momentum.
• Clear governance for responsible AI usage, data handling, model evaluation, and human oversight.
• Strong partnership with domain AI leaders, including successful integration of AI operations work into the broader AI strategy.

We consistently monitor external market data and update base salary ranges accordingly.  We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience.  In addition to our base salary offerings, we also provide equity grants for all new hires. $180,000-$250,000. Note: This role is located in Boston, MA and requires you to be on-site 5 days per week. 

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.