Principal, Back-Office AI Transformation

The Principal, Back-Office AI Transformation owns hands-on delivery of Five9’s internal back-office AI automation agenda. This individual-contributor role belongs to someone who does the work directly: they scope a use case, build or stand up the automation, and prove out the value, rather than direct others to do it. As pilots convert into a scaled program, we expect this role to grow into building out the team behind it: forward-deployed engineers and process professionals, human and agentic.
The mandate has three connected parts:

• Run the diagnostic as an ongoing discipline. Baseline and reassess opportunities continually, drawing on employee input, process observation, and benchmarking, to keep the portfolio pointed at real value outcomes.
• Deliver the pilot: a bounded, evidence-generating pilot in a priority workflow, through to measured results.
• Build the blueprint and roadmap so Five9 can mobilize the next pilot and scale what works.

Throughout, you’re held to the same discipline the diagnostic itself demands: you separate real business impact (cost, capacity, quality, speed) from time-savings claims that don’t hold up.
You partner with Business Technology on tooling, with the leaders of Finance, HR, Legal, IT, and other back-office functions whose work is under review, and with any outside delivery partners brought in for a specific phase. The goal is durable internal capability, not outside dependency.
The right person has built or shipped an automation, workflow, or AI-native tool inside a real back-office function, and is as comfortable running the underlying analysis as pairing with an engineer on the build. They partner with finance, HR, legal, and technology organizations and understand how those teams operate day to day, beyond how they appear in an org chart.

Key Responsibilities

AI Readiness Diagnostic

• Build the opportunity inventory by combining existing initiatives, structured employee input, and direct process observation into a single, comparable view of where AI and automation can change back-office work.
• Assess readiness across what determines whether an opportunity is fundable: process and workflow, data, technology and integration, talent and operating model, and governance, beyond where the potential value looks biggest.
• Surface change readiness alongside the opportunity itself, treating early listening and engagement as the first step in adoption rather than an afterthought.
• Define the ontology and context graph for each function in scope: the semantic layer, metric definitions, and function-specific intelligence layer that make the diagnostic and every pilot after it usable. Work with the business to define the ontology and with Business Technology to set the right graph architecture across the organization.

• Own end-to-end delivery of a bounded pilot in a priority back-office workflow, from process discovery and future-state design through a small, controlled user trial with real tasks and human oversight.
• Distinguish demonstrated pilot results from projected benefits at scale, and report what was tested, who used it, and where the evidence has real limits.
• Translate pilot learning into the next blueprint by defining the future workflow, human-AI handoffs, build tasks, and approvals needed to mobilize the following pilot.

• Turn diagnostic findings into a ranked, fundable portfolio, evaluated against agreed criteria for value, readiness, difficulty, risk, and time to value.
• Build the sequenced roadmap: ownership, dependencies, and resourcing for the opportunities that follow the first pilot.
• Keep the underlying model current by updating assumptions as functions validate or challenge the data behind it.

• Define the right measure for each opportunity: cash savings, avoided cost, released capacity, or quality and speed improvements, rather than converting time saved directly into dollars.
• Establish baselines before a pilot starts, agreed with the function owner, so results are credible on the way out as well as the way in.
• Build the evidence packages leadership uses to make investment decisions, clear about what’s proven versus what’s projected.

• Partner with Finance, HR, Legal, IT, and other back-office leaders and the organizations they lead, serving as the connective role between the diagnostic, the pilot, and the people whose work is changing.
• Work alongside Business Technology on environment, access, and integration needs, and with any outside delivery partners engaged for a specific phase, with the goal of leaving Five9 more self-sufficient rather than more dependent.
• Run a lightweight, regular reporting cadence with the Transformation Office and executive stakeholders.

• 15+ years in operations transformation, shared services, business process automation, or an internal strategy/transformation office, with a track record of shipping the work rather than just recommending it.
• Direct experience with one or more back-office functions (Finance/Accounting, HR, Legal, IT, or Procurement) from the inside, not only as an outside advisor.
• Experience running or contributing to a structured organizational diagnostic (employee interviews, process observation, benchmarking) and turning it into a ranked, fundable opportunity portfolio.
• Hands-on experience delivering automation (RPA, workflow tooling, or AI-native applications) from scoping through a measured pilot, beyond evaluating vendors.
• Experience partnering with an internal technology or business-systems team to stand up new tooling, highly recommended.
• Strong quantitative skills, including building and defending a value-measurement approach that separates real business impact from time-savings alone.
• Experience at a public company or in a SaaS/subscription business, highly recommended.
• Comfort managing or partnering with outside consultants or delivery partners on a defined engagement, with a clear bias toward building internal capability rather than lasting dependency.
• Proficiency with AI tools in daily work, with a clear point of view on how they apply to back-office process design and automation.
• Strong written and verbal communication skills, including comfort presenting evidence-based findings to function leaders and senior stakeholders; bachelor’s degree required, MBA or other advanced degree highly recommended.

• You would rather build the thing than write the memo recommending someone else build it.
• You are curious about AI and have a developed point of view on how it will reshape back-office work over time. You have already woven AI into how you work as a tool that changes what is possible, not as a talking point.
• You have deployed multi-player AI use cases, beyond single-user copilots, and can point to teams that got measurably more productive as a result.
• You are comfortable working without a large team around you, and without a fully settled scope on day one.
• You ask “what work is being done here” before you ask “why is this role located where it is.”
• You build trust with the people whose day-to-day work you are studying and proposing to change.
• You would rather show a working pilot than a polished deck.
• You’re comfortable telling leadership what the evidence doesn’t yet show, as well as what it does.