Director, AI First Enterprise Architecture

Director, AI First Enterprise Architecture

Chicago, IL

Direct Hire

Salary Range : $190,000 - $250,000

Benefits : Full benefits start on day 1Company provides an employer match to employee 401(K) contributions by matching 75% of employee contributions on up to 6% of eligible earnings,FTO - flexible time off - no limitIndustry-leading benefits plans

Director, AI Enterprise Architecture

Our client is a well-established, PE-backed technology company serving the business aviation industry. With operations across North America, Europe, and Asia, they support thousands of aircraft globally through a portfolio of software platforms, financial tools, and operational services. The engineering organization is undergoing a full AI-first transformation, and this role sits at the center of that effort.

Position Summary

As Director, AI Enterprise Architecture, you define and own the enterprise architecture vision and standards that shape how the company builds software in an AI-first, agentic engineering model. Reporting to the SVP of Engineering and AI Transformation, you set the reference architectures, API and integration standards, and architectural guardrails that every engineering vertical follows — converting the company’s investment in Claude Code Enterprise and its Microsoft/Azure platform into consistent, secure, and scalable systems.

This is a hands‑on, high‑influence leadership role. You chair the Architecture Review Board (ARB), advocate and uphold shared architecture standards across AI Solution Architects embedded in each engineering vertical, and directly lead two AI Solution Architects. You partner closely with the Directors of Internal and External Apps Engineering so that delivery teams build on common patterns rather than divergent one‑offs.

Success is measured by outcomes: architecture consistency and reuse across the organization, the security and reliability of what teams ship, the speed at which proven patterns spread, and the trust the business places in engineering decisions.

Responsibilities

AI First Enterprise Architecture and Strategy

• Define and own the AI-first enterprise architecture vision, aligning agentic engineering, product platforms, data strategy, and modernization with business priorities.
• Architect enterprise-scale AI ecosystems spanning multi-agent systems, retrieval-augmented generation (RAG) and knowledge platforms, MCP-enabled tooling, model lifecycle management, and AI-assisted SDLC capabilities.
• Establish the Microsoft/Azure-first architecture posture — C#/.NET, ASP.NET Core, React/TypeScript, Azure SQL, Service Bus, Entra ID, Key Vault, App Services, AKS/ACR, and secure CI/CD — as the default for new and modernized systems.
• Operationalize Claude Code Enterprise as a strategic accelerator across specification, code generation, refactoring, testing, documentation, and review.

Architecture Review Board, Standards, and Governance

• Chair the Architecture Review Board, setting agenda, cadence, and decision rights that drive consistent architecture across engineering verticals.
• Define and maintain API design, event-driven, data contract, versioning, and interoperability standards, along with agent behavior boundaries and evaluation frameworks.
• Establish governance for AI-first development: code ownership, review expectations, IP and secrets protection, auditability, approved model usage, and human-in-the-loop accountability — in partnership with Security, Legal, and Infrastructure.
• Ensure responsible AI across everything that ships: fairness, explainability, model monitoring, security posture, and regulatory alignment.

Reference Architectures and Platform Alignment

• Publish and mature reference architectures, architecture decision records (ADRs), reusable patterns, and engineering playbooks.
• Standardize how teams build and consume MCP servers that expose enterprise systems as secure, model-ready tools.
• Define observability, lifecycle management, performance, and resiliency standards that keep production AI systems dependable at scale.
• Drive measurable architecture maturity through ADR discipline, pattern reuse, API consistency, and reduced rework.

Project Intake, Discovery, and Emerging Capability Adoption

• Serve as the architectural intake gate for new initiatives — assessing projects for architectural fit, AI suitability, feasibility, build-versus-buy options, risk, and alignment to enterprise standards.
• Maintain a forward view of the AI and agentic landscape so the organization plans deliberately rather than reacts.
• Run structured discovery, proofs of concept, and capability spikes that validate promising technologies against the Microsoft/Azure stack, security posture, and business needs.
• Define the pathway for accepting proven capabilities into production: vetting, standardizing, and folding new tools and patterns into reference architectures.

Leadership, Mentorship, and Stakeholder Partnership

• Directly lead and develop two AI Solution Architects.
• Guide and influence AI Solution Architects and engineering leaders across verticals through the ARB and technical leadership rather than direct management.
• Stay close enough to the work to prototype, review designs, challenge assumptions, and demonstrate credible hands‑on engineering judgment.
• Build trusted relationships across Business Units, Engineering, Product, Architecture, Security, Infrastructure, Data, and Operations.
• Translate architecture strategy, risks, adoption, and business impact into clear executive-level narratives.

Required Qualifications

Core Experience

• 12+ years in software engineering and architecture, including 5+ years in a solution architect, principal engineer, or enterprise/product architecture leadership role with ownership of system design for production SaaS platforms.
• Demonstrated experience defining architecture strategy for cloud, distributed systems, APIs, integrations, and data platforms at enterprise scale.
• Production-level fluency in the Microsoft stack: C#/.NET, ASP.NET Core, REST APIs, React/TypeScript, SQL Server/Azure SQL, and distributed-systems patterns.
• Hands‑on experience designing and implementing AI‑first, spec-driven (SDD) workflows and agentic systems across the software delivery lifecycle.
• Track record establishing architecture standards, review processes, and governance that improved consistency, security, and delivery speed across multiple teams.
• Proven ability to influence executives and cross‑functional leaders, and to mentor senior architects and engineers through influence rather than direct people management.
• Excellent written and verbal communication skills; able to translate complex technical concepts for technical and non‑technical audiences alike.

AI and Claude Ecosystem Proficiency (Claude Strongly Preferred)

• Hands‑on experience with AI coding agents and agentic workflows — Claude Code strongly preferred; GitHub Copilot, Codex, or equivalent acceptable.
• Hands‑on experience with multi‑agent design patterns (planning, orchestration, observability) and MCP server implementation against enterprise data sources.
• Production expertise with LLM APIs (Claude API preferred): tool use, structured outputs, document processing, streaming, and rate‑limit management.
• Strong prompt engineering skills, including structured outputs and retrieval‑augmented prompting.
• Working knowledge of AI evaluation frameworks (quality, cost, latency) and responsible AI design.

Highly Desired Qualifications

• Experience in aviation, transportation, asset management, maintenance, aftermarket services, or other complex operational B2B domains.
• Experience with Azure AI Foundry, Azure OpenAI, Microsoft Fabric/OneLake, Semantic Kernel, Power Platform, or comparable AI engineering ecosystems.
• Experience modernizing legacy platforms through incremental architecture, API‑led integration, event‑driven patterns, cloud migration, and test automation.
• Familiarity with DORA metrics, SPACE concepts, and developer productivity telemetry.
• Integrations with Dynamics 365 F&O, Salesforce or equivalent CRM, and Microsoft Fabric.
• Experience in regulated, safety‑sensitive, or audit‑heavy environments where security, governance, and operational reliability matter.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent professional experience; advanced degree a plus.