VP/AI & Business Transformation

Harris Computer•Quebec, QC

2d•CA$170,000 - CA$180,000•Remote

About The Position

Harris Lighthouse Group is seeking a Vice President, AI & Business Transformation to accelerate practical AI adoption and business modernization across its portfolio of vertical market software businesses. This is a hands-on leadership role for someone who can move between strategy and execution, working directly with R&D, Product, Professional Services, Support, Sales, and business unit leadership to change how work gets done. The VP, AI & Business Transformation will report directly to the EVP of Lighthouse and serve as a member of the senior leadership team. The role will work across three business units with different markets, products, customer bases, technology stacks, and levels of AI readiness. The right candidate will be able to build trust with technical and non-technical teams, move quickly from diagnosis to prototype, and translate AI opportunity into measurable business results. This person will also become Lighthouse’s AI thought leader, shaping how we use AI internally, how we talk about AI with customers, and how we measure AI adoption, usage velocity, and business impact. This role is ideal for a high-agency leader who wants to build something visible and significant inside an established software portfolio. The right leader will help Lighthouse become deliberate, capable, and documentable in the way AI shows up for employees and customers. Remote/home office eligible. Travel required as needed for business unit, customer, and field engagement.

Requirements

Ability to move between strategy and execution
Ability to build trust with technical and non-technical teams
Ability to move quickly from diagnosis to prototype
Ability to translate AI opportunity into measurable business results
High-agency leader
Willingness to get close to the work, understand the problem, and help build practical solutions quickly
Experience working directly with BU leaders, R&D leaders, Product, Professional Services, Support, Sales, and Operations
Experience assessing current AI adoption, skill levels, workflow maturity, roadblocks, and team readiness
Experience building a portfolio-level AI roadmap
Experience serving as a senior AI thought leader
Experience translating AI strategy into working solutions
Experience helping teams make practical decisions about where AI should improve existing work and where it should enable a fundamentally better way of operating
Experience helping R&D teams accelerate SDLC maturity
Experience supporting disciplined use of AI in planning, development, testing, documentation, release management, and supportability
Experience driving adoption of AI-assisted engineering practices
Experience identifying where AI development tools can improve speed, quality, and consistency
Experience partnering with R&D leaders to determine when AI should be used to improve current development practices and when it should change the way software is designed, built, tested, or delivered
Experience helping teams reduce manual effort, improve throughput, strengthen quality, and create more reliable development habits
Experience building or leading the creation of low-hanging AI solutions that solve immediate operational pain points
Experience developing working examples that help teams see what is possible and create momentum
Experience moving successful pilots into repeatable workflows with clear ownership, adoption plans, governance, and measurement
Experience identifying customer workflow problems where AI agents, copilots, assistants, automation, or embedded intelligence could create clear value
Experience partnering with all departments to turn customer pain points into working AI-enabled solutions
Experience helping teams define when an opportunity should become a pre-built agent, a custom customer solution, a product capability, a services accelerator, or an internal workflow improvement
Experience driving movement from ideation to production, with clear ownership, adoption plans, customer validation, and measurable outcomes
Experience working with customers and field teams to ensure AI solutions are practical, trusted, and aligned with how customers actually work
Experience helping companies demonstrate real AI progress in competitive markets
Experience creating repeatable patterns for customer-facing AI delivery
Experience defining practical AI adoption and usage metrics across a portfolio
Experience measuring outcomes such as cycle-time reduction, development throughput, quality improvement, manual work, faster support resolution, improved PS leverage, better documentation coverage, customer impact, and margin contribution
Experience partnering with BU leaders to ensure AI adoption is tied to operating priorities, financial outcomes, customer value, and competitive positioning
Experience helping leaders understand which behaviors and results matter most when evaluating AI progress
Experience building reporting that is clear, credible, and useful for leadership decision-making

Nice To Haves

Experience with tools such as GitHub Copilot, Claude, Claude Code, ChatGPT, Cursor, Windsurf, Replit, Playwright, MCP-connected workflows, and related AI development tools

Responsibilities

Work directly with BU leaders, R&D leaders, Product, Professional Services, Support, Sales, and Operations to identify the highest-impact opportunities for AI-enabled change
Assess current AI adoption, skill levels, workflow maturity, roadblocks, and team readiness across each business unit
Build a portfolio-level AI roadmap that balances quick wins, long-term operating model change, customer impact, and competitive positioning
Serve as the senior AI thought leader for Lighthouse, helping leaders understand what is possible, what is practical, and what needs to change
Translate AI strategy into working solutions, not just presentations, pilots, or activity reporting
Help teams make practical decisions about about where AI should improve existing work and where it should enable a fundamentally better way of operating
Help R&D teams accelerate to Level 2 and Level 3 SDLC maturity under Harris expectations
Support more disciplined use of AI in planning, development, testing, documentation, release management, and supportability
Drive adoption of AI-assisted engineering practices, including codebase analysis, test generation, automated code review, debugging support, release note generation, documentation generation, and developer onboarding
Identify where tools such as GitHub Copilot, Claude, Claude Code, ChatGPT, Cursor, Windsurf, Replit, Playwright, MCP-connected workflows, and related AI development tools can improve speed, quality, and consistency
Partner with R&D leaders to determine when AI should be used to improve current development practices and when it should change the way software is designed, built, tested, or delivered
Help teams reduce manual effort, improve throughput, strengthen quality, and create more reliable development habits
Spend time inside each BU to understand real problems before prescribing solutions
Build or lead the creation of low-hanging AI solutions that solve immediate operational pain points
Develop working examples that help teams see what is possible and create momentum
Move successful pilots into repeatable workflows with clear ownership, adoption plans, governance, and measurement
Identify customer workflow problems where AI agents, copilots, assistants, automation, or embedded intelligence could create clear value
Partner with all departments to turn customer pain points into working AI-enabled solutions
Help teams define when an opportunity should become a pre-built agent, a custom customer solution, a product capability, a services accelerator, or an internal workflow improvement
Drive movement from ideation to production, with clear ownership, adoption plans, customer validation, and measurable outcomes
Work with customers and field teams to ensure AI solutions are practical, trusted, and aligned with how customers actually work
Help Lighthouse demonstrate real AI progress in competitive markets vendors are working to displace our products
Create repeatable patterns for customer-facing AI delivery so success in one BU or customer account can be adapted elsewhere
Define practical AI adoption and usage metrics across the portfolio
Measure outcomes such as cycle-time reduction, development throughput, quality improvement, manual work, faster support resolution, improved PS leverage, better documentation coverage, customer impact, and margin contribution
Partner with BU leaders to ensure AI adoption is tied to operating priorities, financial outcomes, customer value, and competitive positioning
Help leaders understand which behaviors and results matter most when evaluating AI progress
Build reporting that is clear, credible, and useful for leadership decision-making