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Mid-level metro fullstack AI role with broad skillset and hybrid work, attracting many qualified applicants.
Fullstack and AI enablement skills transfer across software sectors, though ERP domain experience increases sensitivity.
Mandatory 5+ years and 2+ years AI experience plus architectural and cloud skills cause medium strictness.
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Drive practical AI initiative implementations from concept through delivery by collaborating across engineering, product, cloud, security, operations, and business teams.
Develop and maintain reusable AI architectures, design patterns, enablement materials, and contribute to AI governance and responsible AI practices in partnership with various stakeholders.
Create and lead AI training, workshops, and communities of practice to enable teams, plus influence and support AI capability integration and continuous improvement tracking.
5+ years in software engineering, architecture, cloud architecture, or enterprise architecture.
2+ years designing, implementing, or enabling AI and/or machine learning solutions with strong knowledge of Generative AI, LLMs, AI Agents, RAG architectures, and prompt engineering.
Experience with Azure AI Services, OpenAI, Claude, AWS Bedrock, Google Vertex AI, or similar AI platforms.
Strong understanding of AI security, privacy, compliance, responsible AI principles, and operational practices like DevOps and MLOps.
Experienced in leading AI transformation or enablement initiatives within large organizations, including building AI Centers of Excellence.
Skilled in developing enterprise standards, governance frameworks, architectural guidance, and technical enablement for AI adoption at scale.
Strong collaboration and mentoring skills with ability to influence technical and non-technical stakeholders and drive organizational change.