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Mid-level experience band, metro locations, and a generalist solution-engineer title drive high applicant competition.
AI enablement and enterprise architecture focus makes industry transferability moderate, benefiting experienced tech and SaaS candidates.
Explicit 5+ years engineering and 2+ years AI experience plus cloud/ML platform requirements increase shortlisting strictness.
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Lead identification and implementation of practical AI solutions across engineering, product, cloud, security, and business teams from concept to delivery.
Develop and maintain AI reference architectures, solution design patterns, governance, and responsible AI practices including security and compliance.
Create and deliver AI training, workshops, and enablement materials; mentor teams on AI adoption and operational best practices.
5+ years in Software Engineering, Architecture, Cloud Architecture, or Enterprise Architecture.
2+ years designing, implementing, or enabling AI and/or machine learning solutions.
Strong knowledge of Generative AI, LLMs, AI Agents, RAG architectures, prompt engineering, and experience with AI platforms (Azure AI, OpenAI, AWS Bedrock, Google Vertex AI).
Experience with AI governance, security, privacy, compliance, DevOps/MLOps, and operational practices.
Experienced in leading AI transformation or enablement initiatives, including AI Centers of Excellence in large organizations.
Proficient in developing enterprise AI standards, governance frameworks, and architectural guidance for cloud-native SaaS platforms.
Strong capability to influence diverse technical and business stakeholders and drive AI adoption and operational improvements across teams.