Head of Product & AI Transformation

📋 Description

• • As the Head of Product & AI Transformation at Valsoft Corporation, you will spearhead a critical initiative to modernize Thermeon, a leading rental management system (RMS) with a decades-long legacy and a global clientele. This pivotal role is designed to harness the power of Artificial Intelligence to revolutionize how our software is developed and delivered, creating significant value for our customers and driving internal efficiencies.
• • Your primary mandate will be to lead the comprehensive modernization of Thermeon's codebase. This involves a strategic, phased migration of core COBOL modules to contemporary programming languages, meticulously preserving all existing business logic. You will leverage cutting-edge AI-assisted tools, such as Claude Code, to accelerate the extraction, documentation, and translation of this legacy code, ensuring a smooth and efficient transition.
• • A key aspect of this modernization is validating functional equivalence through rigorous parallel-run testing before any cutover, guaranteeing the integrity and reliability of the system. You will be instrumental in establishing modern Continuous Integration/Continuous Deployment (CI/CD) practices and adopting API-first patterns, which will significantly enhance future development speed and robustness.
• • Furthermore, this role aims to broaden the platform's technical foundation, reducing its dependence on scarce COBOL expertise. This strategic shift will alleviate hiring and onboarding constraints, enabling faster delivery of new features and improvements.
• • Beyond codebase modernization, you will be accountable for optimizing the custom development pipeline. This involves owning the entire process from scoping client requests and writing precise specifications to collaborating closely with the engineering team for timely and successful delivery. You will establish clear visibility into development capacity, enabling confident client commitments and minimizing delays.
• • A crucial part of your responsibility will be partnering with sales and customer success teams to ensure custom work is accurately scoped and priced, reflecting its true value to the client. By leveraging the speed gains from modernization, you will systematically reduce cycle times for client-specific projects, enhancing customer satisfaction and loyalty.
• • With a modernized and more capable platform, the next strategic priority is to develop agentic AI-powered tools and workflows that rental operators will find indispensable and be willing to pay for. This requires a deep understanding of the intricacies of rental business operations, including fleet management, reservations, check-in processes, yield management, and damage workflows.
• • You will conduct structured discovery sessions with operators to identify the highest-value AI opportunities and validate their willingness to invest. Building robust business cases for each initiative, quantifying potential revenue uplift or cost savings for the operator, will be essential. You will then spec, ship, and meticulously measure the outcomes of each AI solution, tracking real-world operator results post-launch.
• • Target areas for agentic product development include yield and rate optimization agents to maximize revenue per available vehicle, fleet utilization and rebalancing agents to prevent idle-vehicle revenue loss, and automation for check-in and check-out processes to reduce counter time and staffing costs.
• • Additional opportunities lie in predictive maintenance agents to minimize unplanned downtime, upsell and cross-sell agents to enhance the customer journey, and damage detection and claims automation to mitigate revenue leakage.
• • The role also encompasses an internal AI transformation initiative. You will apply an AI-first approach to internal functions, auditing processes across Product, Engineering, Sales, Customer Success, Finance, and Operations to identify high-value automation opportunities and prioritize them based on ROI.
• • You will build and deploy AI agents to eliminate repetitive manual work across the organization and train teams on effective AI tool usage, establishing appropriate governance guardrails to ensure responsible implementation.
• • Success at 6 months includes initiating a modernization pilot with a clear roadmap, improving custom development pipeline predictability, and developing a prioritized map of agentic opportunities with at least one solution in development. By 12 months, modernization should demonstrably reduce development cycle times, at least one client-facing agentic solution should have shipped with documented ROI, release delays should be materially reduced, and internal AI automations should be live across multiple functions.