Three-minute read
Product and Technical Program Manager specializing in AI, automation, and digital platforms
I lead technology and automation initiatives from initial requirements through development, testing, launch, and ongoing improvement.
01
Professional summary
I am a product and technical program manager. I take work a business is running by hand — campaign delivery, client intake, loan servicing, prospect research, analytics reporting — and turn it into a product with defined requirements, automated steps, tested releases and reporting the business can act on.
For the last decade I have run my own business and built the technology behind it: an email marketing platform and delivery engine in production, an AI platform for the agency's own operations, and the controls that decide what an AI agent is allowed to do to a live system. Before that I spent four years consulting inside financial institutions on requirements, system integration and user acceptance testing, defect management and release readiness.
02
Roles I am targeting
All five come down to the same work: define the problem, own the delivery, and decide what should be automated and what should not.
- Product Manager
- Program Manager
- Technical Program Manager
- Product Operations Manager
- AI Product Manager
New York, NY · Remote. Open to selected consulting engagements alongside permanent roles.
03
Selected outcomes
Percentage figures are self-reported from Liorry's own delivery records and come from different engagements. The enterprise figures are program facts from the resume, not results attributed to Liorry alone. The discovery figure is measured directly from platform records, deduplicated by address.
170+
Clients served
Cumulative client base delivered through a business I founded and scaled to six figures.
Source: Self-reported.
$45m
Technology program
Supported discovery and planning — problem definition, business case, requirements, roadmaps, risks, vendor evaluation and steering committee reporting.
Source: Resume — Moody's engagement, 2014–2015.
17,000+
Financial advisors served
Analytics and content-distribution platform, including a Tableau dashboard delivered for regional sales directors and owned after rollout.
Source: Resume — Morgan Stanley engagement, 2013–2014.
70%
Fewer manual workflows
Share of recurring manual operational steps eliminated across intake, production and reporting.
Source: Self-reported.
50%
Faster development cycles
Time from a written requirement to a tested production release, under a documented AI-assisted development workflow with automated checks.
Source: Self-reported.
40%
Faster project turnaround
Total delivery time, after client intake, briefing and production handoffs moved onto the AI platform.
Source: Self-reported.
300K+
Contacts discovered monthly
Unique, publicly published business contact addresses found and screened automatically in a single 30-day period. Every address still passes human review before it can enter a sending list.
Source: Measured from platform records, July 2026.
04
Three projects that cover the range
One enterprise delivery engagement, one product I own, one program I led. Between them they cover requirements, testing, automation and running a system in production.
- Status: Shipped2011 — 2015
Enterprise Technology Programs in Financial Services
Where the delivery discipline comes from: requirements, SIT and UAT, defect management and business sign-off inside four financial institutions.
- Business problem
- Large financial institutions cannot ship a change on confidence. Requirements have to be agreed, testing coordinated, defects resolved and retested, and the business outcome confirmed before release.
- My role
- Business analyst and delivery consultant across four institutions — requirements, testing coordination, defect management and business validation.
- Solution
- One repeatable sequence — map the process, document requirements, plan and coordinate SIT and UAT, drive defects to closure and retest, validate the outcome, support a controlled release.
- Outcome
- Supported discovery on a $45m program, analytics reaching 17,000+ advisors, and Loan IQ and back-office delivery across the loan-servicing lifecycle.
- Status: Production2023 — present
AI-Powered Business Operations Platform
Product ownership of a new operating model: AI handling production work, a person accountable for every client commitment.
- Business problem
- An agency running on a handful of repeated workflows — qualify an inquiry, produce content, produce creative, report — each performed by hand, each as slow as whoever was free.
- My role
- Founder, product owner and operations lead — vision, requirements, prioritization, delivery coordination and day-to-day operation.
- Solution
- An operating model where AI handles intake acknowledgment, drafting and creative production, with fixed rules for routing and scoring, and a person accountable for every client commitment.
- Outcome
- 170+ clients served, 70% fewer manual workflows, 40% faster project turnaround, 45% lower creative production cost, first qualified response under two minutes.
- Status: Production2025 — present
Modernizing a Legacy Marketing Platform
Program leadership on a live revenue system: compliance checks built into the process, delivery problems handled automatically, and releases that separate deploying code from switching a feature on.
- Business problem
- A campaign operation that worked until it quietly stopped being correct — compliance checks duplicated across send paths, delivery problems escalating faster than anyone noticed, and interrupted sends resolved by an operator's judgment call.
- My role
- Product owner and program lead — vision, requirements, architecture decisions, delivery coordination, testing, release planning and production operations.
- Solution
- One unsubscribe and bounce check that every send passes through, a barrier that blocks a send until its readiness checks complete, automatic delivery protection, recovery that resumes an interrupted send from its own records, and every change behind a switch that is off by default.
- Outcome
- Compliance built into the process, delivery incidents handled without waiting for someone to notice, interrupted sends resumed automatically, and 50% faster requirement-to-production cycles.
05
Product and program capabilities
Grouped by the kind of work rather than listed as keywords, so it is clear what each one is for.
Product Management
- Discovery
- Product requirements
- PRDs
- Roadmaps
- Prioritization
- User stories
- Acceptance criteria
- Product metrics
- Launch planning
Program Delivery
- Workstream planning
- Timelines
- Dependencies
- Risks
- Budgets
- Vendors
- Stakeholder alignment
- SIT and UAT
- Defect management
- Release coordination
AI and Automation
- AI-assisted workflows
- Process automation
- Human approval steps
- Permission and approval controls
- Audit trails
- System monitoring
- Business rules
- Responsible AI boundaries
On AI specifically: I use AI to improve analysis, recommendations and productivity, while keeping approvals, permissions and critical business rules inside reliable software workflows. High-impact actions require a person to approve them.
06
Enterprise background
Four consultant engagements in financial-services technology between 2011 and 2015. Separate programs, separate sponsors, one delivery pattern.
Moody's Investor Services
2014 — 2015
Business Analyst, Information Technology
Discovery and planning on a technology program with an approximately $45 million budget. I documented the business case and requirements, coordinated roadmaps with vendors and internal divisions, tracked program risks, scored every vendor proposal for procurement, and prepared the bi-weekly steering committee reporting.
Morgan Stanley
2013 — 2014
Business Analyst, Insights & Analytics, Wealth Management
Analytics and content distribution to more than 17,000 financial advisors. I gathered targeting requirements, worked with big-data developers on enterprise queries, led a small offshore team delivering a Tableau dashboard through UAT and rollout, then owned weekly reporting for its users.
Credit Suisse
2011 — 2012
Business Analyst, Consultant — Loan IQ, Back-Office Technology Delivery and Reference Data
Loan IQ and back-office functions across the loan-servicing lifecycle. I gathered requirements, mapped processes and data flows, wrote test cases, coordinated SIT and UAT, managed defects through resolution and retesting, and validated the business outcome before delivery. I also supported reference-data and settlement-related systems.
Société Générale
2012
FX Exotic Trade Support
High-volume financial operations on a desk trading illiquid currencies — daily reporting on positions and problem trades, correction of mis-booked and un-booked trades ahead of valuation, and resolution of breaks and risk items with the investigations team.
That is the three-minute version
If it fits what you are hiring for, email is the quickest next step. If you would rather read further first, every case study covers the decisions, the testing and the parts that did not work.