Bachelor's Degree (BS/BA) + 5-7 years of experienceDemonstrated experience designing, implementing, or securing AI/ML workloads in cloud environmentsHands-on proficiency with primary AI/ML platforms: Amazon Bedrock, Amazon Q, and Amazon SageMakerPreferred experience with secondary platforms: Azure AI Foundry, Microsoft 365 Copilot, Copilot Studio, Azure Machine LearningExperience in a client-facing consulting or professional services roleEmbraces emerging technologies, including AI tools, to work smarter, solve problems, and drive better business outcomesBasic Python competency, including the ability to read, write, and troubleshoot code for automation and integration tasksUnderstanding of agentic AI patterns, AI governance frameworks, and secure AI composition (e.g., multi-agent orchestration, tool-use guardrails, prompt injection mitigation)AWS Certified Solutions Architect, AWS Certified Machine Learning, or AWS AI Practitioner certificationAzure AI Engineer Associate, Azure Solutions Architect Expert, or Microsoft 365 Certified: Administrator ExpertGoogle Cloud Professional Machine Learning Engineer or Google Cloud Professional Cloud ArchitectExperience writing statements of work (SOWs), proposals, or scoping documents for professional services engagementsBackground in security frameworks (NIST AI RMF, OWASP LLM Top 10, ISO 42001) as applied to AI/ML workloadsPublic speaking experience, including presentations at conferences, webinars, or industry eventsPrior experience in practice development, service catalog creation, or go-to-market strategy for a consulting or professional services firmAWS Certified Developer - AssociateExperience with AI gateways, Model Context Protocol (MCP), and policy-as-code frameworks (e.g., Cedar, OPA)
Bachelor’s degree in Computer Science, Engineering, or related discipline; equivalent experience acceptable.CERTIFICATES, LICENSES, REGISTRATIONS REQUIRED:
