AI Adoption Lead @ FINN Partners
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About the Role
The AI Adoption Lead at FINN Partners is integral in bridging advanced AI capabilities with everyday business solutions. You will support employees in implementing AI-powered tools and drive the design and delivery of automations that eliminate manual work, optimize processes, and boost productivity.
Key Responsibilities
- Training & Enablement: Develop workshops, playbooks, and digital resources to raise AI literacy among all employees.
- Change Management: Lead structured change management initiatives in collaboration with HR and communications.
- Workflow Analysis: Map processes, quantify inefficiencies and strategize high-impact automation opportunities.
- Governance & Security: Ensure ethical, secure, and compliant use of AI and champion responsible practices.
- Continuous Optimization: Track usage, user sentiment and business impact to refine AI solutions regularly.
Qualifications
Candidates must have at least 3 years experience with AI/ML technologies, specifically with generative AI models such as Gemini, OpenAI, and Claude. Experience in prompt engineering, technical training, AI adoption, and change management is essential. Strong communication and interpersonal skills are required to translate complex technical ideas to non-technical audiences.
Why Join FINN Partners?
Be at the forefront of AI innovation, impact organizational efficiency and empower 1300+ employees. This role offers continuous learning, a collaborative environment, and an opportunity to shape the future of AI adoption.
Key Skills/Competency
- AI Adoption
- Training Design
- Change Management
- Workflow Analysis
- Automation Strategy
- Governance
- Ethical AI
- Stakeholder Collaboration
- Prompt Engineering
- Technical Training
How to Get Hired at FINN Partners
🎯 Tips for Getting Hired
- Customize Your Resume: Tailor your skills to AI adoption and training.
- Highlight Relevant Experience: Emphasize generative AI, change management, and automation expertise.
- Research FINN Partners: Understand their culture, achievements, and global reach.
- Prepare for Technical Insights: Review AI, ML models, and prompt engineering principles.
- Practice Communication: Be ready to explain complex AI concepts simply.