Manager, Digital & AI Engineering

MAG Aerospace•Fairfax, VA

About The Position

The Manager, Digital & AI Engineering serves as the primary transformation engine for the enterprise. This leader designs and delivers the digital capabilities — spanning custom applications, applied AI, enterprise data architecture, workflow automation, and DevSecOps — that translate technology investment into measurable business and mission outcomes. This is a working director role in a lean IT organization. You will be expected to set direction, build and mentor a team, and deliver hands-on results simultaneously. You will partner closely with the Lead Architect, the Cybersecurity Manager, and executive stakeholders to ensure that every capability built is secure, compliant, and adopted.

Requirements

10+ years of progressive experience in data architecture, cloud engineering, or digital solution architecture, with at least 3 years in a senior technical leadership role
Demonstrated experience owning and executing an enterprise data strategy — including data governance frameworks, data catalog implementation, quality standards, and data democratization programs
Proven track record delivering cloud-native solutions on Microsoft Azure or equivalent hyperscaler platform; fluency with Azure data, AI, and integration services
Hands-on experience designing and implementing CI/CD pipelines and DevSecOps practices in an enterprise environment
Experience building and deploying applied AI or ML capabilities in a production enterprise context — including integration of AI models into business workflows
Experience migrating legacy data warehouses or enterprise applications to cloud-native platforms
Experience advising C-level or senior executive stakeholders on data and AI strategy — translating technical complexity into business value
Cloud data and integration platforms: Azure (Data Factory, Synapse, Azure AI Services, Azure OpenAI), and/or equivalent (GCP BigQuery, Dataflow, Vertex AI, Pub/Sub) — deep expertise in at least one, working knowledge of both preferred
Data architecture patterns: relational, dimensional, NoSQL, event-driven, and streaming architectures at enterprise scale
AI/ML integration: experience deploying and governing LLM-based solutions, RAG systems, and AI agents in enterprise workflows
DevSecOps toolchain: CI/CD pipeline design using Git-based workflows, Python automation, and infrastructure-as-code practices
Data governance and cataloging: hands-on experience with enterprise data catalog tools (e.g., Microsoft Purview, Dataplex, Alation, or equivalent) and governance program design
Integration architecture: API design, microservices, event-driven patterns, and enterprise application integration
Demonstrated ability to lead cross-functional initiatives, influence without direct authority, and drive organizational change in complex environments
Exceptional communication skills — able to present technical strategy to executive audiences and work-level detail to engineering teams with equal clarity
Experience managing vendor relationships and technology contracts
S. Citizenship required — non-negotiable for CMMC Level 2 compliance and GCCH access
Must be able to pass background investigation and meet suitability requirements for clearance processing
Must be willing to comply with all CMMC-mandated security practices applicable to this role, including annual security awareness training, CUI handling protocols, and system use agreements
Must agree to and comply with enterprise acceptable use, data handling, and AI use policies

Nice To Haves

Experience leading enterprise AI adoption initiatives (Generative AI, copilots, automation)
Familiarity with CMMC requirements and their operational implications for application development, data handling, and CI/CD environments
Experience building enterprise data governance programs, data catalogs, stewardship models, and quality frameworks
Experience leading migration from legacy or on-premises platforms to modern cloud-native architectures
Familiarity with Power Platform (Power Automate, Power Apps) for low-code automation and workflow transformation
Experience with CMMI Level 3 (Development or Services) or working within defined, documented, and measured engineering processes
Knowledge of agentic AI frameworks and multi-agent orchestration patterns (e.g., Semantic Kernel, AutoGen, LangChain)
Experience operating in a lean IT organization supporting a large, geographically distributed user base
Experience working in a U.S. Government contractor (GovCon) environment or other regulated environments

Responsibilities

AI Enablement & Enterprise Strategy Define, communicate, and execute the enterprise AI strategy — identifying high-value use cases, building the adoption roadmap, and delivering AI-enabled capabilities that improve operational efficiency and decision-making quality
Integrate AI into enterprise workflows through copilots, intelligent agents, and decision-support tools built on the Azure AI ecosystem within the GCCH environment
Evaluate, govern, and manage the deployment of AI models and services — ensuring responsible use, CUI compliance, and alignment with enterprise security policy
Serve as the organization's primary technical advisor on AI and data to executive and senior leadership, translating complex capabilities into clear business value and investment rationale
Data Architecture & Engineering Own and maintain the enterprise data architecture — including data models, integration patterns, ingestion pipelines, and data quality frameworks across structured and unstructured sources
Design and operate retrieval and knowledge systems (RAG architectures, vector stores, enterprise search) that directly enable AI applications
Establish and enforce enterprise data governance standards — including data classification, lineage, stewardship roles, and lifecycle management — in coordination with Cybersecurity for CUI-specific handling requirements
Enable data democratization: build the tools, catalogs, and processes that make trusted data accessible to analysts and business stakeholders across the organization
Application Engineering & Lifecycle Management Own the enterprise application portfolio — overseeing custom development, internal tooling, SaaS governance, and lifecycle management for all applications in the IT portfolio
Ensure application security baselines are met from design through deployment, in coordination with the Cybersecurity pillar (shift-left DevSecOps principles)
Manage SaaS vendor relationships and application integrations, ensuring solutions meet CMMC compliance requirements and GCCH hosting standards where applicable
Automation & Workflow Transformation Identify and execute process automation opportunities across the enterprise — using Power Platform, scripting, and AI agents — to reduce manual overhead and improve operational consistency
Partner with business units to map, redesign, and automate high-volume, error-prone workflows; quantify and report impact to leadership
DevSecOps & Engineering Practice Design, implement, and operate CI/CD pipelines that embed security controls, compliance checks, and automated testing directly into the development lifecycle
Champion engineering best practices — code reviews, automated testing, infrastructure-as-code, and deployment automation — consistent with CMMI Level 3 process standards
Establish and maintain development standards, toolchains, and environment governance across the team
Represent Digital & AI Engineering in the Monthly Architecture Review Board; contribute to cross-pillar reference architecture and AI governance standards governed by Enterprise Architecture
Participate in CMMC assessment preparation — providing documentation, evidence, and technical review for practice areas related to configuration management, system and communications protection, and audit/accountability within application and data systems
Contribute to IT vendor evaluation and contract input for data, AI, and application platforms — particularly tools requiring GCCH compliance or CUI handling certification
Support the Change Advisory Board (CAB) as the application and data domain owner for change review and risk assessment
Develop and maintain the pillar's contribution to the enterprise System Security Plan (SSP), including system boundary documentation for all applications and data assets in CMMC scope
Mentor and develop pillar team members; contribute to hiring, onboarding, and retention efforts for the broader IT organization