Senior Manager, Care Operations

evermore

3h•$144,630 - $154,260•Remote

About The Position

Reporting to the Sr. Director, Member Operations, you will help operate and continuously improve the operating model for evermore’s Customer Care function. This is a hands-on build, and uniquely modern operations role: you will help design, deploy, and continuously improve the agentic Care system: voice and chat AI agents, agent-assist for human reps, automated knowledge retrieval, and AI-driven QA, alongside the human workforce that handles what AI cannot. This role has breadth, driving how Care scales by contributing across vendor strategy, the AI agent stack, the workforce model (humans and agents), technology infrastructure, the learning system, and the analytics layer. You will help shape the annual roadmap for Care, including deflection and automation targets, AI safety and compliance posture, and cost-to-serve trajectory. You will support budget planning and unit economics, and contribute to client QBRs and operating reviews. You will partner closely with peers across Operations, Implementation, Finance, Product, Strategy and Solution Development, Marketing, Engineering, and Account Management, and especially closely with AI/ML and Product on the agentic Care roadmap. The ideal candidate is a Care operator who has worked inside a multi-vendor contact center AND has built or operated production AI agents in a customer support setting, able to move fluently between operations, regulated-environment requirements, and the technical realities of deploying LLM-based systems.

Requirements

7–10 years of experience in contact center or care operations, including time leading programs or small teams of individual contributors.
Direct experience deploying and operating AI in a customer support or contact center environment: voice or chat AI agents, agent-assist copilots, AI-driven QA, or automated knowledge retrieval, including ownership of the production quality bar, not just sponsorship of someone else's pilot.
A working understanding of how modern LLM-based agentic systems are built and evaluated: retrieval, tool use, guardrails, eval sets, online metrics, red-teaming, human-in-the-loop review, sufficient to be a credible operating partner to AI/ML and Product.
Experience owning a multi-vendor BPO environment at scale, and a point of view on how vendor partnerships and human roles evolve as AI scales inside Care.
A track record of building and scaling Care operations in a healthcare, Medicare Advantage, Medicaid, or benefits administration environment: including the compliance, PHI handling, member communication, and audit requirements that govern operating AI agents in a regulated setting.
Demonstrated experience executing an operating plan: contributing to the model, building the roadmap, helping manage the budget, and reporting on results to executive stakeholders.
Experience leading the learning, knowledge, and quality function within a Care organization, with a clear point of view on how the knowledge base, training, and QA programs change when AI agents are part of the workforce.
Strong analytics orientation and fluency with the data systems Care runs on, including the AI-specific layer of deflection, containment, AI quality, and cost-per-resolution.
An operator who can move fluently between strategy and execution.
A systems thinker who connects dots across operations, quality, training, technology, AI, and finance.
Strong written and verbal communication skills.
A clear passion for, if not direct experience in, addressing health inequities.
Commitment to building a psychologically safe environment and diverse culture that is highly collaborative, strives to set and achieve goals together, and embraces transparency, innovation, and accountability.
A leader who invests in the people around them, including the humans whose roles evolve as AI scales, and who coaches and holds the bar with the same standards they expect of others.

Responsibilities

Driving Care Operations Programs: Helping shape the Care operating model, the mix of internal teams, BPO partners, and AI agents; the channel strategy; the technology stack; and the quality framework, and translating it into a quarterly roadmap with clear owners, milestones, and success metrics.
Leading cross-functional program teams across operations, AI / agentic Care, training and knowledge, and quality, partnering with team leads, coaching individual contributors, and holding the bar on execution.
Modeling Care unit economics: cost-to-serve across human and AI handling, programs, and channels, and recommending where to deploy AI, where to keep humans, where to consolidate vendors, and where to renegotiate.
Serving as an operational voice for Care, contributing to internal operating reviews, client QBRs, and new business pursuits, including the AI Care agenda.
Designing and Operating the Agentic Care System: Owning the AI agent roadmap for Care: voice and chat agents for member and caregiver self-service, agent-assist copilots for human reps, automated triage and routing, AI-driven knowledge retrieval, and AI-led QA, and partnering with Product and Engineering on what to build vs. buy.
Defining the human + AI operating model: what gets routed to an AI agent, what escalates to a human, how handoffs happen, how AI agent capacity and confidence thresholds are managed alongside human workforce planning, and how the experience stays cohesive to the member.
Establishing the evaluation and quality framework for AI agents: offline eval sets, online metrics, red-teaming, human review sampling, and the calibration cadence between AI QA and human QA so the bar is the same regardless of who (or what) handled the contact.
Owning the safety, compliance, and policy posture for agentic Care, including the guardrails, escalation triggers, audit logging, and PHI handling required to operate AI agents inside CMS-regulated programs such as Medicare Advantage and Medicaid.
Leading the change management for AI in Care: how human agents are trained to work alongside AI, how their roles and incentives evolve as automation scales, and how the vendor partnerships are restructured as the human/AI mix shifts.
Driving the AI agent improvement loop: pulling failure cases out of production, partnering with AI/ML and Product on prompt, policy, retrieval, and model updates, and shipping measurable quality gains release over release.
Owning the Vendor Strategy and Human Workforce Performance: Setting the vendor strategy: partner selection, scope allocation, geographic mix, and commercial terms, and leading periodic RFPs, contract renewals, and SOW negotiations with BPO partners as their scope evolves alongside AI deflection.
Establishing the performance framework across ACT, Startek, and other partners: SLAs, scorecards, governance cadence, and escalation paths, and owning day-to-day vendor relationships at the operations and director level.
Directing Workforce Management strategy across humans and AI agents: joint forecasting and capacity planning, intraday operating standards, AI fallback plans, and the cross-channel playbook for peak events, launches, and recovery scenarios.
Leading the most complex operational initiatives: platform migrations, AI agent rollouts, large new client launches, market entries, and turnaround plans, and owning the cross-functional execution with Product, Implementation, Engineering, and Customer Success.
Building the Learning, Knowledge, and Quality System for a Hybrid Workforce: Setting the strategy for how Care builds capability across humans AND AI agents: the onboarding model, the ongoing development curriculum, and the certification standards that govern who (or what) is qualified to handle each program and channel.
Owning the Care knowledge architecture: recognizing that the knowledge base is now both human-facing documentation and the retrieval source for AI agents, and ensuring content governance, structure, and freshness meet the bar for both audiences.
Defining the unified quality program: calibration cadence, coaching frameworks, and the link between QA outcomes and reinforcement learning for humans, plus the analogous loop of failure analysis and model/prompt/policy updates for AI agents.
Driving the Data, Technology, and AI Agenda for Care: Defining the metrics that matter for Care, including the AI-specific layer of deflection rate, AI containment, escalation rate, AI quality, hallucination rate, and cost-per-resolution across human and AI handling, and ensuring the analytics function produces a defensible, accurate narrative for every audience.
Owning the Care technology roadmap: Salesforce (Service Cloud), telephony (e.g., Vonage), contact center platforms (e.g., Zendesk), WFM tools, LMS and authoring (e.g.,EasyGenerator), knowledge platforms (e.g., Confluence), and the AI agent / agent-assist / AI QA stack, and partnering with IT, Engineering, Product, and AI/ML on selection, implementation, and continuous improvement.
Serving as a credible operational presence for health plan clients: leading client-facing performance conversations, walking clients through the AI Care model and its safeguards, contributing to new client onboardings, and acting as a senior escalation point for operational issues.

Benefits

Medical, Dental, and Vision insurance with 90% paid employer premium contributions for all tiers
100% Employer Paid Short-Term & Long-Term Disability
100% Employer Paid Basic Life Insurance Policy
Employee Assistance Program (EAP)
401(k) Program
Discretionary PTO
Paid holidays
Parental Leave
Flexible work schedule within core hours
Work anywhere in the USA as we are a fully distributed team from coast to coast