Cloud Platforms and Agentic AI Architect
About The Position
Drive the architecture, design, and delivery of scalable, multi-cloud AI systems and API-driven, event-based applications. Lead teams in integrating structured and unstructured data to build Lakehouse architectures and support retrieval-augmented AI pipelines. Establish API governance and multi-cloud LLM routing using Azure APIM or AI Gateway. Oversee cloud infrastructure provisioning and full-stack observability across Azure and AWS environments. Guide end-to-end ML lifecycle implementation, from ingestion through training, deployment, and traceability, and promote modern agentic delivery practices. Mentor teams, drive technical excellence, and support public-health aligned mission needs with empathy and strong leadership instincts.
Requirements
- 10+ years of experience leading enterprise IT and software delivery programs, including cloud migration or modernization
- 8+ years of experience designing Azure or AWS cloud architectures
- 5+ years of experience building API-first, microservices-based, and event-driven applications such as Azure Service Bus and Event Grid
- 3+ years of experience implementing AI, ML, or knowledge-based systems, including agentic workflows, RAG pipelines, ontology-driven architecture, and vector search
- Experience in Azure AI Search and PostgreSQL PgVector, including conceptualizing vector index strategies for varied use cases
- Experience with Azure APIM or AI Gateway to enable secure API exposure and multi-cloud model routing, including Azure OpenAI, Bedrock, and partner LLMs
- Experience designing and implementing full-stack observability for applications, microservices, and AI agents using Azure Monitor, App Insights, and OTel for telemetry, tracing, and cost visibility
- Experience with cloud infrastructure provisioning and operations across Azure, including AKS, Container Apps, App Service, Functions, Logic Apps, and Storage, and AWS
- Experience with end-to-end ML lifecycle workflows, including ingestion, feature engineering, training, deployment, cataloging, drift tracking, and Azure Databricks, for Lakehouse integration and delta sharing
- Bachelor’s degree
Nice To Haves
- Experience implementing ML workflows within enterprise or public-health environments
- Experience leading technical delivery teams
- Knowledge of microservice API orchestration, caching strategies, and secure API exposure patterns
- Knowledge of multi-cloud AI access models and architectural integration patterns
- Knowledge of responsible AI, data ethics, privacy, and security best practices
- Possession of strong communication skills
- Master's degree in CS, Management Information Systems, or IT
- Azure or AWS Certifications
Responsibilities
- Drive the architecture, design, and delivery of scalable, multi-cloud AI systems and API-driven, event-based applications.
- Lead teams in integrating structured and unstructured data to build Lakehouse architectures and support retrieval-augmented AI pipelines.
- Establish API governance and multi-cloud LLM routing using Azure APIM or AI Gateway.
- Oversee cloud infrastructure provisioning and full-stack observability across Azure and AWS environments.
- Guide end-to-end ML lifecycle implementation, from ingestion through training, deployment, and traceability.
- Promote modern agentic delivery practices.
- Mentor teams, drive technical excellence, and support public-health aligned mission needs with empathy and strong leadership instincts.
Benefits
- health, life, disability, financial, and retirement benefits
- paid leave
- professional development
- tuition assistance
- work-life programs
- dependent care
- recognition awards program
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
