The posting
About the Job
The AI Operations Manager is responsible for leading the ongoing performance, quality, optimization, and evolution of digital and voice bot programs. This role serves as the primary partner-facing point of contact and leads a cross-functional team that may include Bot Quality Analysts, Data Analysts, Prompt Designers, and Bot Configuration and Development resources.
The AI Operations Manager translates bot performance data, quality findings, operational feedback, and customer experience observations into clear insights and prioritized recommendations. They own the operating cadence for the program, coordinate enhancement delivery, manage the change backlog, and measure the impact of improvements over time.
This role is both strategic and operational. The AI Operations Manager ensures that current bot performance is understood, issues are acted on, enhancements are delivered effectively, and a clear roadmap exists for future capability expansion.
As AI Operations & Optimization Manager, You Will…
Serve as the primary partner-facing point of contact for all bot performance, quality, optimization, and enhancement activities while leading the overall operating rhythm (including weekly business reviews, monthly performance reviews, and quarterly executive reviews).
Build strong working relationships with Client Partners, Operations, CX, Product, Technology, Analytics, and other key stakeholders, managing incoming partner requests and coordinating cross-functional support.
Lead, direct, and set clear priorities for a multidisciplinary AI operations team (including Bot Quality Analysts, Data Analysts, Prompt Designers, and Configuration resources) to align effort toward common goals, continuous improvement, and measurable outcomes.
Support the evaluation and calibration of Copilot, Agent Assist, RTG, and other AI-supported agent experiences across channels, partnering with Operations, CX, and Quality teams to align on standards.
Diagnose whether performance opportunities are driven by persona and conversational behavior, prompt design, workflow configuration, knowledge sources, policies or operating procedures, system integrations, or data availability and quality.
Prioritize recommendations and proposed backlog changes based on customer impact, business impact, risk, frequency, effort, expected benefit, and quantified operational metrics.
Own and maintain the bot enhancement backlog.
Coordinate enhancement delivery across Bot Quality, Prompt Design, Bot Configuration, Development, Analytics, Operations, and other support teams.
Manage change control, approvals, release coordination, testing requirements, and stakeholder communication.
Ensure enhancements are documented with clear objectives, expected outcomes, and success measures.
Track recommendations from identification through approval, implementation, validation, and closure.
Coordinate User Acceptance Testing with Bot Quality Analysts, Operations teams, and partner stakeholders.
Establish and maintain reporting across bot performance, resolution, quality, experience, and compliance.
Track key performance indicators such as containment and deflection, resolution rate, bot satisfaction and quality scores, intent-level performance, compliance, escalations, contact volume, and automation utilization.
Monitor performance by intent, channel, use case, and customer journey to identify areas requiring additional attention.
Measure performance before and after enhancements to determine whether recommended changes produced the expected outcome.
Build trend reporting to demonstrate ongoing performance improvements and identify emerging opportunities.
Manage the operating rhythm for bot governance.
Leverage performance data, contact volume, customer intents, quality observations, and operational insights to build and maintain an AI optimization roadmap.
Identify opportunities for expanding automation into new intents and customer journeys.
Maintain a catalog of recommended future intents and automation opportunities.
Assess prospects for expanded integrations, workflows, knowledge sources, personalization, and transactional capabilities.
Partner with Product, Technology, Operations, and partner stakeholders to prioritize future bot capabilities.
Balance short-term optimization with long-term AI strategy and capability expansion.
Review agent operating procedures, policies, knowledge resources, FAQs, and other reference content used by bots and agents.
Enhance bot knowledge coverage, accuracy, accessibility, and consistency.
Recommend revisions to knowledge assets when inaccurate, incomplete, outdated, or unclear content impairs bot performance.
Align bot workflows and knowledge repositories with current business processes and customer policies.
Provide day-to-day guidance and direction to a multidisciplinary AI operations team.
As AI Operations & Optimization Manager, You Need…
5+ years of experience across BPO, customer experience (CX), operations, client services, quality assurance, analytics, continuous improvement, program management, or related disciplines.
Proven track record of leading cross-functional teams and orchestrating initiatives across Operations, Quality, Analytics, Technology, Training, and Product.
Strong client and executive stakeholder management experience, serving as a primary point of contact while managing expectations, strategic priorities, risks, and deliverables.
Experience analyzing operational performance data to extract actionable insights, build business cases, and execute targeted intervention plans.
Demonstrated ability to establish and drive an operational cadence, including weekly performance reviews, action tracking, KPI reporting, and Executive Business Reviews.
Proven ability to prioritize competing initiatives based on customer impact, ROI, operational risk, and resource constraints.
Advanced presentation and storytelling skills, with the ability to clearly articulate what happened, why it matters, recommended next steps, and measurable outcomes of interventions.
End-to-end change management experience guiding initiatives from initial opportunity identification through operational rollout and impact measurement.
Rigorous organizational skills and the ability to maintain clear ownership, manage interdependencies, and track timelines across complex workstreams.
Ability to synthesize quantitative metrics, qualitative observations, stakeholder feedback, and technical diagnostic findings to uncover root causes and emerging trends.
The capability to distill complex technical, AI, and analytical data into concise, high-impact narratives and recommendations tailored for diverse audiences.
Strong leadership skills to cultivate trusted partnerships, resolve ambiguity, facilitate executive decision-making, and align cross-functional teams around shared KPIs.
The capacity to balance competing roadmaps, resources, and dependencies to keep delivery teams focused on high-value, needle-moving initiatives.
A deep sense of ownership and accountability to drive initiatives end-to-end from initial insight to verified business impact.
An inquisitive mindset to challenge legacy assumptions, probe operational friction, test solutions, and iteratively drive continuous process optimization.
A solid foundational understanding of conversational AI architecture, bot capabilities, dialogue workflows, knowledge bases, and AI quality metrics to effectively lead and coordinate technical and operational specialists.
