Director/Managing Director, AI Software Development

CohnReznick• , TX

21h•Remote

About The Position

As CohnReznick grows, so do our career opportunities. As one of the nation’s top professional services firms, CohnReznick creates rewarding careers in advisory, assurance, and tax with team members who value innovation and collaboration in everything they do! CohnReznick helps organizations optimize performance, manage risk, and maximize value through CohnReznick LLP (assurance services) and CohnReznick Advisory LLC (advisory and tax services). Together, the firm provides leaders with deep industry knowledge and relationships, solutions to address clients’ unique business goals and risks, and insight on how emerging market forces can drive opportunity. With offices nationwide, the firm serves organizations around the world as an independent member of Nexia. We currently have an exciting career opportunity for a Director/Managing Director, AI Software Development to support our Global Digital & Cybersecurity practice. CohnReznick is a hybrid firm and most of our professionals are located within a commutable distance to one of our offices. This position is considered remote which means it does not require job duties be performed within proximity of a CohnReznick office location. However, as a remote employee, you may be required to be present at a CohnReznick office with scheduled notice for client work, team meetings, or trainings. YOUR TEAM. The Director / Managing Director, AI Software Development is a senior technology leader responsible for establishing and leading CohnReznick's software engineering capability. This position defines the vision, strategy, operating model, talent plan, architecture, and delivery approach for AI-enabled products, platforms, and solutions across the firm. The position is accountable for building a high-performing AI-native software development organization capable of delivering proprietary technology assets that create sustainable competitive advantage. The leader oversees the design, development, deployment, and operation of AI-powered applications, intelligent automation solutions, agentic workflows, and client-facing digital products. This is not a traditional application-development leadership role. The successful candidate must have personally built and scaled a native AI software team from inception through production delivery, including recruiting specialized talent, establishing engineering and governance standards, and delivering secure applications with measurable business impact.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent relevant experience.
Fifteen or more years of progressive software engineering and technology leadership experience.
Seven or more years leading software development organizations, including leaders of engineering teams.
Five or more years delivering AI-enabled applications, machine learning platforms, intelligent automation solutions, or generative AI products.
Demonstrated success creating and scaling a native AI software development organization that moved beyond pilots and experimentation to secure, production-grade solutions.
Proven delivery of enterprise-grade software products and platforms in complex, regulated, or high-trust environments.
Experience leading geographically distributed teams and a blended workforce of employees, contractors, and strategic partners.
Generative AI, large language models, agentic architectures, retrieval-augmented generation, AI evaluation, observability, and model operations.
Cloud-native software development, enterprise application architecture, APIs, integration patterns, data platforms, and analytics ecosystems.
DevSecOps, CI/CD, automated testing, software supply-chain controls, production reliability, and secure development lifecycle practices.
Responsible AI, AI governance, privacy, security, model risk, data governance, and human oversight.
Product-oriented delivery using measurable outcomes, iterative development, user feedback, adoption measures, and value realization.

Nice To Haves

Advanced degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Business, or a related field.
Leadership experience in professional services, financial services, regulated industries, or enterprise B2B software.
Experience with Microsoft Azure AI, Azure OpenAI, Microsoft Copilot technologies, and modern AI engineering frameworks.
Relevant credentials in AI, cloud architecture, software engineering, cybersecurity, or product delivery.
Experience commercializing proprietary software or creating client-facing digital products and technology-enabled services.

Responsibilities

Define and execute a multi-year AI software engineering strategy aligned with firm business and technology objectives.
Establish the vision, roadmap, investment priorities, and operating model for the GDC AI development capability.
Identify opportunities to create proprietary software assets that improve client service, quality, efficiency, growth, and professional experience.
Advise executive leaders and governance forums on opportunities, investments, risks, dependencies, and portfolio performance.
Recruit, organize, develop, and retain a multidisciplinary team of AI engineers, software engineers, machine learning engineers, technical leads, and architects.
Define job architecture, role expectations, career paths, leadership spans, technical communities, and talent-development practices for the AI engineering function.
Create an engineering culture centered on innovation, responsible experimentation, accountability, inclusion, collaboration, and disciplined production delivery.
Build a sustainable talent pipeline and develop future engineering leaders.
Lead AI-enabled products, platforms, and solutions from discovery and architecture through engineering, release, adoption, operation, and continuous improvement.
Partner with Product Management and business stakeholders to translate strategic priorities into sequenced, funded, and measurable delivery commitments.
Manage execution across concurrent initiatives while balancing value, speed, quality, security, risk, reliability, and maintainability.
Establish outcome, delivery, quality, adoption, and operational measures; use results to improve priorities and execution.
Establish development standards, reference architectures, engineering frameworks, reusable components, testing practices, and technical quality controls.
Define patterns for large language model integration, agentic systems, retrieval-augmented generation, intelligent workflow automation, observability, evaluation, and model operations.
Implement modern cloud-native engineering, DevSecOps, CI/CD, API, integration, reliability, incident-management, and lifecycle-management practices.
Promote reuse, platform leverage, technical-debt management, and reduction of unnecessary technology redundancy.
Embed security, privacy, legal, regulatory, records-management, data-governance, and responsible AI requirements throughout the development lifecycle.
Partner with Enterprise Architecture, Information Security, Data & Analytics, Risk, Legal, and other control functions to govern design and deployment decisions.
Communicate complex technical matters in clear business terms and build trusted relationships with executives, professionals, clients, vendors, and strategic partners.
Drive adoption, change leadership, knowledge transfer, and transparent reporting of progress, risks, decisions, and realized value.