Senior Azure AI Solutions Architect / Engineer

GovCIO; Annapolis (MD); À distance; USD 150 000 - 230 000; Plein temps

Résumé du poste

GovCIO is seeking a senior Azure AI Solutions Architect/Engineer to lead enterprise AI initiatives for a federal environment. You will design and implement AI-driven document intelligence, enterprise search, and RAG capabilities within a secure, scalable architecture.

You will work across Azure OpenAI, Azure AI services, and Foundry, collaborating with application, data, and infrastructure teams to productionize prototypes and transfer knowledge to existing staff.

Qualifications

• Experience delivering enterprise AI solutions in a federal/complex environment.
• Hands-on with Microsoft Azure AI services and Foundry platform.
• Ability to design secure, scalable architectures across apps and data.
• Proven ability to integrate AI capabilities with existing enterprise systems.

Responsabilités

• Lead architecture, design, development, and deployment of enterprise Generative AI solutions on Azure.
• Implement Azure AI services, including OpenAI models, AI Search, and Document Intelligence.
• Architect Retrieval-Augmented Generation (RAG) over structured and unstructured data.
• Develop AI-assisted enterprise search, QA, summarization, and information extraction capabilities.
• Design semantic, vector, and hybrid retrieval approaches to meet business needs.
• Create secure integration patterns with existing applications, APIs, and databases.
• Embed AI functionality into applications via REST APIs, SDKs, and Java services.

Connaissances

Generative AI

Azure AI

Architectural design

Enterprise search

NLP / Document Intelligence

RAG / retrieval

Outils

Azure Foundry

Azure OpenAI

Azure AI Search

Azure Document Intelligence

REST APIs

SDKs

Java services

Description du poste

United States; Washington, Washington, DC

Suitability/Public Trust

Fully remote

Software Engineering Services

Overview

GovCIO is currently hiring for a highly experienced, hands‑on Senior Azure AI Solutions Architect / Engineer to lead the architecture, development, and implementation of enterprise Generative AI and intelligent document solutions within a complex federal application environment.

This individual will serve as a technical leader for the adoption of Microsoft Azure AI capabilities, working alongside existing application architects, developers, infrastructure teams, and subject matter experts to introduce secure, scalable AI capabilities into established enterprise systems.

Initial efforts will focus on AI‑assisted document intelligence, enterprise search and retrieval, Retrieval‑Augmented Generation (RAG), document summarization, structured data extraction, document classification, and AI‑assisted business process automation.

The successful candidate must be equally comfortable designing the architecture and building the solution. This is not solely an advisory or strategy position. The individual will be expected to configure Azure AI services, develop prototypes and production solutions, integrate with existing applications and data repositories, troubleshoot technical challenges, establish AI development patterns, and transfer knowledge to existing technical teams.

The position is remote and supports a federal customer in the Washington, D.C. metropolitan area.

Responsibilities

• Lead the architecture, design, development, and implementation of enterprise Generative AI solutions using the Microsoft Azure AI ecosystem.

• Design and implement solutions using Microsoft Foundry, Azure OpenAI/model services, Azure AI Search, Azure AI Document Intelligence , and related Azure capabilities.

• Architect and implement Retrieval‑Augmented Generation (RAG) solutions over enterprise structured and unstructured data.

• Develop AI‑assisted enterprise search capabilities capable of identifying relevant documents, pages, data elements, and supporting evidence across large document repositories.

• Develop capabilities for natural‑language question answering, document summarization, information extraction, structured output generation, and AI‑assisted research.

• Design and implement semantic, vector, hybrid, and agentic retrieval approaches as appropriate for specific business requirements.

• Develop secure integration patterns between Azure AI services and existing enterprise applications, APIs, databases, and document repositories.

• Integrate AI functionality into existing enterprise applications through REST APIs, SDKs, Java services, and other approved integration patterns.

• Evaluate and implement Azure AI Document Intelligence capabilities for document classification, metadata/data extraction, confidence scoring, and exception handling.

• Design AI agents and orchestration workflows using Microsoft Foundry capabilities when appropriate.

• Partner