Head of Shared Services Operations (Miami, FL)

Extenteam Careers•Miami, FL

4d•$137,000•Onsite

About The Position

Extenteam serves short-term rental property managers through Shared Services, our 24/7 contact center operation handling guest communication, escalations, and operational workflows across 60,000+ properties. We're building a team of doers and self-starters - hands-on, agile, tech-savvy. People who push for automation, refuse to solve problems by adding headcount, and improve processes through data. The Head of Shared Services owns the systems, structures, and economics that make Shared Services run well and scale profitably. The operational layer underneath owns day-to-day SLA, CSAT, AHT, scheduling, and quality. You own whether those metrics are achievable, whether they're improving, and whether the unit economics make sense as we grow. You report to the Head of Operations and will be exposed to the founder, leadership team, and enterprise clients directly.

Requirements

7+ years in operations leadership, including one role running a service operation at scale (contact center, shared services, or similar)
Hands-on experience designing automation-ready workflows, knowledge bases, or decision trees
Strong grasp of how operational data is captured,and reported
Demonstrated ability to build new revenue streams or commercial programs within an operations context
Cross-functional experience with Product, Engineering, Finance, and Revenue
Must be within commutable distance of Miami, FL or willing to relocate. In-office role
Communicate exceptionally well in writing
Self-motivated and decide under uncertainty without losing momentum
Set up your own tools and figure things out
Make others around you better

Nice To Haves

Short-term rental, hospitality, real estate, or property management ops experience
SaaS or tech-platform business going through a services-to-product transformation
Cognitive analyst with contact center / CX exposure, or a former consultant or startup operator who owned a CX account
Deploying AI in production operational environments, including governance and trust mechanisms
Designing commercial programs (upsell systems, pricing models, partner success frameworks) that tie ops performance to revenue
Leading a service org through a model transition

Responsibilities

Shared Services Charter with each enterprise client (decision rights, sign-off requirements, SLA penalties on either side)
Workforce model: capacity planning, shift modeling, and staffing economics for a 24/7 multi-time-zone operation
Client SLA governance on enterprise accounts (escalations, QBRs, SOP delivery)
Knowledge base infrastructure: clean source of truth with named owners per partner, review cadence, and partner-specific variants.
Data quality: spot when a number is wrong before it drives a wrong decision
Cost-per-property model and gross margin trajectory as the book scales
The migration arc from human-led to AI-led workflows: what moves, on what timeline, with what proof points
Deployment and performance of Autopilot AI inside Shared Services. Drive the false-negative rate on AI escalations toward zero - a trust metric, not just an accuracy metric
The bridge between feature release and team adoption. When Product ships, you make sure the team uses it well, not just receives it
Two-way connection between agents and Product. Capture field signal, translate to product input, close the loop back
Customer conversations. Spend time with property manager partners directly and bring their pain into the operation and roadmap
New revenue streams: service categories, upsell programs, partner-facing products that scale without proportional headcount
Pricing frameworks, capacity models, and business cases for new offerings
Automation default. Every recurring task is a candidate for a system. Ask "can this be a system?" before "can this be a person?"
Make the team capable of more. Every workflow, tool, and automation should expand what a single agent can handle. Headcount is the last lever
Lead through your operational layer. Set the standards, build the structures, hold the layer underneath accountable. Don't bypass the contact center manager to run individual agent performance yourself
Hands-on. Open a dashboard, read a ticket, sit in on a call, walk through a workflow yourself
Finance: cost modeling, unit economics, FY P&L for Shared Services
Product and Engineering: operational input grounded in agent data and partner outcomes
Head of Revenue: pricing, service tiers, account expansion
Partner Success: real-time account health and predictive risk signals
Vendors: Aircall, Breezeway, Guesty integrations and similar tooling