AI Modernization Manager

The Role

You'll be embedded with a fast-growing platform in the payments and commerce space, serving thousands of merchants across physical and digital gift card programs. This role owns discovery, planning, and coordination for a modernization program, transforming undocumented legacy applications, scripts, and manual processes into a structured roadmap for engineering teams to build against. AI will be central to your daily workflows—not just for individual tasks but for creating reusable workflows for discovery, documentation, planning, and risk tracking.

Key Responsibilities

• Technical and business discovery: Investigate legacy applications, scripts, and manual processes to understand their purpose, dependencies, and behavior. Document how these systems function and maintain a comprehensive knowledge base.
• Modernization planning: Assess each capability to determine whether it should be kept, replaced, consolidated, automated, or retired. Develop and maintain a prioritized roadmap aligned with real business priorities and deadlines.
• Delivery and stakeholder coordination: Oversee initiatives from discovery through release and handover. Collaborate across engineering, QA, operations, business stakeholders, managed service providers (MSPs), and external partners.
• Operational readiness and risk management: Ensure all shipped deliverables include requirements, documentation, monitoring, and assigned ownership. Track and resolve material risks.
• Continuous improvement and AI-enabled workflows: Convert recurring manual tasks across discovery, planning, development, QA, release, and maintenance into reusable, AI-assisted workflows for documentation and risk tracking.

Requirements

• 7+ years of experience in product management, technical discovery, systems analysis, legacy modernization, or a similar hybrid technical/delivery role, with product management experience as a must-have.
• Experience with application architecture, APIs, databases, integrations, reporting, scheduled jobs, and both cloud and on-prem infrastructure.
• Proven ability to reverse-engineer poorly documented systems by reading code, interviewing stakeholders, and reconstructing context without relying on pre-existing documentation.
• Capacity to translate business and operational needs into actionable requirements, plans, architecture diagrams, runbooks, and monitoring/support handoff documentation.
• Understanding of software delivery, release management, observability, support, and operational handover to hold engineering teams accountable.
• Excellent written and verbal communication skills, with experience bridging engineering teams, business stakeholders, and external partners.
• Willingness to challenge missing information or assumptions.
• Hands-on experience using AI for investigation, analysis, documentation, or workflow improvement—not just theoretical familiarity.
• Ability to read and evaluate .NET code and architecture, ask critical questions, and sanity-check engineering deliverables, even without writing production code.

Bonus Points:

• Experience with transaction systems or reporting platforms.
• Experience with Windows-based legacy applications and hybrid (cloud + on-prem) infrastructure.
• Experience working with or managing relationships with a managed service provider (MSP).

Qualities for Success

• Proactive investigator: You dig into systems and people to uncover undocumented context and keep questioning until clarity is achieved.
• Decisive planner: You can analyze messy capabilities and make informed decisions about keeping, replacing, consolidating, or retiring them.
• Documentation-minded: Diagrams, runbooks, and written context are integral to your problem-solving approach.
• Cross-functional communicator: Equally effective when discussing architecture with engineers or business impact with stakeholders.
• AI-fluent: You build reusable AI workflows for discovery and documentation but verify AI outputs against real sources.

Where You’ve Likely Developed These Skills

• Technical product management, systems analysis, or legacy modernization roles in complex environments (e.g., fintech, payments, retail tech, or platforms undergoing modernization).
• Roles requiring reverse-engineering systems with minimal or no documentation.
• Consulting, agency, or professional services backgrounds where rapid trust-building with internal teams was critical.

You’re a Great Fit If You

• Enjoy the detective work of uncovering how systems actually function beyond surface-level descriptions.
• Already integrate AI into your investigative, documentation, and planning processes and want to institutionalize these workflows for your team.
• Are comfortable challenging and verifying technical outcomes without designing or building them yourself.

This Role is Not a Fit If You

• Prefer working from a fully specified backlog rather than building the picture yourself.
• Are uncomfortable reading code or working directly with technical systems.
• Have only superficial familiarity with AI tools rather than hands-on experience in investigation or documentation.