Cloud Platforms and Agentic AI Architect

Booz Allen Hamilton•Atlanta, GA

2d•$142,900 - $266,000•Remote

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.