VP of Software Engineering and AI

Blue Signal Search; Tempe (AZ); On-site; USD 250,000 - 350,000; Full time

Job summary

Blue Signal Search is seeking an accomplished engineering executive to turn AI ambition into working technology and to lead a software organization through its next stage of modernization. This VP of Software Engineering and AI will stay deeply involved in architecture, engineering decisions, and delivery while shaping how AI is applied across the business.

In this role you will drive executive ownership of the software organization, collaborate with senior business, product, and data leaders,

Qualifications

• Demonstrated success moving AI to production with measurable impact.
• Hands-on leadership balancing strategy and technical delivery.
• Proven experience with .NET enterprise environments and modernization of legacy systems.
• Strong architecture, API, distributed systems, and cloud experience.
• Clear executive communication and business acumen for resource planning and investments.

Responsibilities

• Turn AI opportunities into production capabilities that improve products and operations.
• Lead AI initiatives from evaluation through deployment, measurement, and continuous improvement.
• Balance executive leadership with hands-on involvement in architecture and engineering decisions.
• Own an established custom software environment, including .NET applications.
• Modernize technology to improve scalability while protecting critical systems.
• Set priorities across AI adoption, platform modernization, and reliability.

Skills

AI production deployment

Engineering leadership

.NET/enterprise software

Legacy modernization

Software architecture

Cloud technologies

AI platforms evaluation

Executive communication

Team development

Tools

.NET Framework

Job description

Our client is looking for an accomplished engineering executive who can turn AI ambition into working technology and lead a software organization through its next stage of modernization. This is not a role for an AI strategist who operates from the sidelines. The company needs an AI executor who has personally helped move AI capabilities into production and can remain deeply involved in architecture, engineering decisions, and delivery. The VP of Software Engineering and AI will have significant influence over how the organization applies AI, evolves its established technology environment, and builds the engineering capabilities required for future growth.

This Role Offers

• Executive ownership of a software engineering organization at a meaningful point of technology transformation.
• A highly visible mandate to move practical AI initiatives from opportunity to production and measurable business impact.
• The opportunity to modernize an established custom technology environment while protecting the systems the business relies on today.
• A leadership role designed for a builder who wants to remain technically engaged rather than transition entirely into administration.
• Direct collaboration with senior business, product, and data leaders on technology priorities and investment decisions.
• Significant influence over engineering practices, architecture, talent development, technology partnerships, and the long term evolution of the software organization.

Focus

• Turn high value AI opportunities into production capabilities that improve products, workflows, decision making, and operational efficiency.
• Lead AI initiatives from technical evaluation and prototyping through integration, deployment, measurement, and continuous improvement.
• Balance executive leadership with hands on involvement in architecture, engineering decisions, and complex technical challenges.
• Take ownership of an established custom software environment, including .NET applications and systems developed by previous teams.
• Modernize inherited technology to improve scalability and maintainability while protecting the reliability of business critical systems.
• Set engineering priorities across AI adoption, platform modernization, technical debt, reliability, security, and ongoing business needs.
• Partner with product, data, and business leaders to translate company priorities into executable technology initiatives and measurable outcomes.
• Strengthen engineering practices across software delivery, testing, deployment, observability, security, and operational readiness.
• Evaluate AI platforms, development tools, vendors, and external solutions based on practical implementation needs and business value.
• Develop engineering leaders and senior technical talent while creating a culture focused on experimentation, accountability, continuous learning, and execution.

Skill Set

• Demonstrated success implementing AI in production environments, with clear examples of solutions personally built, deployed, integrated, or operationalized.
• Hands on engineering leadership experience, with the ability to balance organizational leadership and meaningful technical execution.
• Strong experience with .NET and enterprise software development environments.
• Proven ability to inherit unfamiliar legacy or custom built applications, understand their architecture, and successfully improve or modernize them.
• Approximately 12 or more years of progressive software engineering experience, including substantial responsibility for engineering leadership and technical delivery.
• Experience modernizing established software platforms while maintaining reliability and continuity for business critical operations.
• Strong knowledge of software architecture, APIs, distributed applications, cloud technologies, data integration, and contemporary engineering practices.
• Experience moving AI, machine learning, generative AI, or intelligent automation initiatives beyond experimentation and into sustained production use.
• Proven ability to develop engineering managers, architects, and senior technical contributors while establishing high standards for execution and technical quality.
• Strong executive communication and business acumen, including the ability to explain complex technology decisions and contribute to resource planning, vendor evaluation, and technology investments.