AI Enablement Lead Jobs
AI Enablement Lead jobs are open across technology, financial services, healthcare, and consulting, from mid-level practitioner to director, with specializations in generative AI adoption, change management, and workforce upskilling. Scan the live roles below and apply to whichever ones fit.
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Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent. That belief was championed by a group of community activists we still honor today as the “12 Angry Seniors.” Their mission continues to guide everything we do.
Today, SCAN is a nonprofit health organization serving more than 500,000 people across Arizona, California, Nevada, New Mexico, Texas, and Washington, with over $8 billion in annual revenue. With nearly five decades of experience, we have built a distinctive, values-driven platform dedicated to improving care for older adults.
Our work spans Medicare Advantage, fully integrated care models, primary care, care for the most medically and socially complex populations, and next-generation care delivery models. Across all of this, we are united by a shared commitment: combining compassion with discipline, innovation with stewardship, and growth with integrity.
At SCAN, we believe scale should strengthen—not dilute—our mission. We are building the future of care for older adults, grounded in purpose, accountability, and respect for the people and communities we serve.
The Job
In this role, you will help advance SCAN’s AI enablement and enterprise data governance practices. This role is responsible for improving the trust, usability, and business context richness of data that powers AI, analytics, reporting, and operational decision-making.
This role helps build the foundation for enterprise AI by strengthening core knowledge management capabilities via the development, governance, and adoption of enterprise data assets and knowledge structures, including business glossaries, governed metrics, semantic layers, ontologies, knowledge graphs, metadata, lineage, and stewardship practices. You will work closely with data stewards, subject matter experts, platform teams, and executive business leaders to build context, standardize business terminology, improve data quality, and make enterprise data easier for people and AI-enabled tools to understand and use.
This is an essential role as SCAN modernizes its data ecosystem through a modern platform, scalable self-service analytics, and AI-assisted ways of working.
You Will
- Enhance SCAN’s semantic foundation by developing dimensional models, hierarchies, domain relationships, and governed metrics that enable consistent AI use cases.
- Support ontology and knowledge graph initiatives by identifying key business entities, relationships, synonyms, and domain concepts that improve data connectivity, searchability, and AI comprehension.
- Govern and document data assets across Snowflake, Databricks, and Iceberg environments to ensure structured and semi-structured data is well-described, discoverable, and trusted for analytics and AI workflows.
- Maintain and enrich the enterprise data catalog, documenting metadata, lineage, ownership, usage context, and business meaning for high-value data assets.
- Improve data discoverability and usability through tagging, glossary management, workflow optimization, and metadata quality controls.
- Perform data and metric validation to assess accuracy, completeness, aggregation logic, consistency, and timeliness across data products, including via the use of AI-assisted tools.
- Partner with business stakeholders, data stewards, subject matter experts, analytics teams, and technical teams to execute enterprise data governance and AI-readiness priorities across key domains.
- Investigate data quality issues, conduct root cause analysis, document business impact, and partner with data engineering, analytics, reporting, and business teams to support resolution.
- Participate in Agile ceremonies to ensure governance and AI enablement work is visible, prioritized, and delivered effectively.
- Drive continuous improvement in governance automation, stewardship workflows, reporting certification, and AI-assisted governance capabilities.
- We seek Rebels who are curious about AI and its power to transform how we operate, improve decision-making, and serve our members.
- Actively support the achievement of SCAN’s Vision and Goals.
- Other duties as assigned.
Your qualifications
- Bachelor's degree in information systems, Data Analytics, Computer Science, Business Administration, Healthcare Administration, Statistics, or a related field; equivalent experience may be considered.
- 3+ years of experience in data engineering, data governance, data management, data quality, analytics, business intelligence, metadata management, knowledge management, or related data-focused role.
- Experience in the health care industry, especially in areas such as Medicare Advantage, clinical analytics, medical economics, quality, pharmacy, claims, provider, member, or operational data environments, is strongly preferred.
- Experience with modern knowledge management techniques such as semantic layers, ontologies, knowledge graphs, retrieval-augmented generation, AI-assisted documentation, or metadata-driven discovery preferred.
- Familiarity with modern warehouse and open Lakehouse concepts, including cloud object storage, open table formats such as Apache Iceberg or Delta Lake, metadata catalogs, data sharing, lineage, and governance of structured and semi-structured data.
- Familiarity with using AI-assisted tools to improve documentation, analysis, data discovery, metadata quality, and governance workflows.
- Experience with enterprise data catalog, metadata management, data lineage, business glossary, stewardship, and/or or report certification practices.
- Experience with BI and reporting platforms such as Power BI, Tableau, SSRS, or similar tools.
- Experience with CLI tools such as Cortex Code, Claude Code, or similar.
- Experience working in SAFe Agile or another Agile delivery framework.
- Preferred certifications include CDMP, DGSP, DCAM, DAMA-related training, Snowflake certification, Microsoft Power BI certification, or relevant Agile/SAFe certifications.
Competencies
- Knowledge Management Mindset: Helps organize business meaning, definitions, relationships, ownership, and metadata so that enterprise data is easier to find, understand, govern, and reuse.
- Business Partnership: Builds trusted relationships with business and technical stakeholders and translates governance, data quality, and AI-readiness practices into business value.
- Analytical Thinking: Uses structured analysis to evaluate data issues, identify root causes, assess business impact, and improve trust in data used for analytics and AI-enabled capabilities.
- Governance Discipline: Applies consistent standards for definitions, metadata, quality rules, stewardship, lineage, and documentation.
- Communication: Explains complex data concepts clearly to both technical and non-technical audiences.
- Continuous Improvement: Identifies opportunities to improve governance workflows, data usability, automation, AI-assisted documentation and scalable self-service analytics.
Skills & Abilities
- Ability to support semantic layer and metrics governance, including standardized definitions, dimensional concepts, hierarchies, measure consistency, and policy adherence.
- Familiarity with knowledge management concepts such as ontologies, knowledge graphs, taxonomies, and domain models.
- Ability to translate technical data structures into clear, business-aligned definitions and documentation, especially via data dictionaries, catalog entries, report inventories, data quality findings, and usage context.
- Strong SQL skills for data profiling, validation, reconciliation, and issue investigation.
- Familiarity with Snowflake, SQL Server, Power BI, Tableau, SSRS, data catalogs, modern analytics platforms, and open lakehouse concepts such as cloud object storage, open table formats, metadata catalogs, and governed data access.
- Ability to work effectively across business, analytics, data engineering, platform, stewardship, and leadership teams.
- Practical understanding of healthcare data domains such as claims, membership, providers, clinical operations, pharmacy, quality, utilization management, or finance preferred.
- Ability to manage multiple priorities in an Agile environment while maintaining attention to detail.
- Awareness of emerging automation, AI-assisted documentation, data quality monitoring, semantic search, and governed by self-service analytics capabilities.
What's in it for you?
Base Salary Range: $80,300 to $138,330 annually
An annual employee bonus program
Robust Wellness Program
Generous paid-time-off (PTO)
11 paid holidays per year, 1 floating holiday, birthday off, and 2 volunteer days
Excellent 401(k) Retirement Saving Plan with employer match
Robust employee recognition program
Tuition reimbursement
An opportunity to become part of a team that makes a difference to our members and our community every day!
We're always looking for talented people to join our team! Qualified applicants are encouraged to apply now!
At SCAN we believe that it is our business to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects our community through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more.
SCAN is proud to be an Equal Employment Opportunity and Affirmative Action workplace. Individuals seeking employment will receive consideration for employment without regard to race, color, national origin, religion, age, sex (including pregnancy, childbirth or related medical conditions), sexual orientation, gender perception or identity, age, marital status, disability, protected veteran status or any other status protected by law. A background check is required.
#LI-JB1 #LI-Hybrid
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. 41 CFR 60-1.35(c)
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Who's Hiring



Top Industries Hiring
- Technology & Software
- Staffing & Recruiting
- Consulting & Professional Services
- Automotive
- Biotechnology & Pharmaceuticals
What Employers Look For
The qualifications that appear most often in AI enablement lead jobs.
- Experience designing and delivering AI adoption programs for enterprise or mid-market teams
- Proficiency with generative AI tools such as large language model platforms and AI coding assistants
- Background in instructional design, organizational change management, or workforce development
- Ability to measure and report AI adoption metrics, productivity gains, and training effectiveness
- Strong facilitation and communication skills for both technical and non-technical stakeholders
- Bachelor's degree in a relevant field such as business, education, computer science, or organizational development
Tips for Your AI Enablement Lead Job Search
Quantify AI adoption outcomes on your resume
Hiring managers for ai enablement lead roles want to see adoption rates, time-to-competency numbers, and productivity gains, not just tool names. Replace generic bullets with before-and-after metrics tied to AI rollouts you led or supported.
Distinguish enablement from adjacent titles
Job postings for this role often blur with AI trainer, AI program manager, and digital transformation lead. Read each description carefully to confirm the role centers on building human capability with AI tools, not just deploying or governing them.
Apply early to roles that fit
Migrate Mate lists ai enablement lead openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Tailor your portfolio around change, not tools
Bring evidence of how you moved reluctant teams to consistent AI use, not just a list of platforms you know. A one-page case study showing adoption curve, intervention, and outcome lands better than a tools matrix for most hiring committees.
Prepare for a live enablement exercise
Many ai enablement lead interviews include a skills scenario where you design a short training module or facilitation plan on the spot. Practice explaining a complex AI concept to a non-technical audience out loud, not just in writing.
Negotiate scope alongside compensation
AI enablement leads often start with unclear authority over tooling decisions and training budgets. Before accepting an offer, confirm in writing which teams you own, what your approval authority covers, and how success is measured in the first year.
AI Enablement Lead Jobs: Frequently Asked Questions
Which companies are hiring the most ai enablement leads?
The companies hiring the most ai enablement leads right now include Humana, Protiviti, and JPMorganChase, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of November 2026. Demand is concentrated in technology, consulting, and financial services organizations running large-scale AI transformation programs.
How many ai enablement lead jobs are remote?
About 85% of ai enablement lead openings are fully remote or hybrid as of November 2026, reflecting how much of this work centers on virtual facilitation and async learning design. Sub-specializations in curriculum development and self-serve AI training content tend to be the most remote-friendly, while roles tied to hands-on team coaching lean toward hybrid or on-site.
How do you become an ai enablement lead?
Start by building a foundation in instructional design, change management, or a technical field where you have used AI tools in real workflows. Move into enablement by leading an AI adoption initiative, even informally, within your current organization. Document adoption outcomes, then target roles at companies actively scaling AI use. Certifications in AI literacy programs or change management frameworks strengthen your candidacy at the director level.
How do you get hired as an ai enablement lead with little experience?
Focus on roles titled AI trainer, AI program coordinator, or change management analyst, which share the same core responsibilities at an earlier career stage. Build a portfolio by volunteering to run an AI tool rollout on your current team, capturing adoption data and participant feedback. Demonstrating that you can move a small group from skepticism to consistent use is more persuasive than credentials alone for most hiring managers in this field.
What does the ai enablement lead interview process look like?
Most processes run three to four rounds, starting with a recruiter screen focused on your background with AI tools and training programs. A hiring manager conversation follows, centered on how you have driven adoption and handled resistance. Many employers then ask for a skills exercise where you design or present a short enablement plan. Final rounds typically involve meeting cross-functional stakeholders such as engineering leads or HR partners whose teams you would support.
Where can I find and apply to ai enablement lead jobs?
You can find and apply to ai enablement lead jobs on Migrate Mate, which lists current openings from across the United States in one place. Search for roles that match your experience level and specialization, then apply directly to each listing that fits your background and goals.
See All 273+ AI Enablement Lead Jobs
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