Customer Support Team Lead - AI Support Operations (Work From Home)

Role Overview

The Customer Support Team Lead – AI Support Operations will be responsible for leading the customer support team while driving the successful implementation, optimization, and expansion of AI-powered customer support conversations.

This role is not only focused on managing human agent performance, but also on improving how AI is used within the support function. The Team Lead will analyze support conversations, identify automation opportunities, improve workflows, create processes, and work closely with internal teams to ensure AI support delivers accurate, efficient, and customer-friendly responses.

You will act as the bridge between the human support team, AI support tools, product/development teams, and customer experience goals.

This is primarily a leadership role managing a team of 7 customer support agents. You’ll mainly be improving AI prompts and responses, similar to using ChatGPT. There’s an AI component, but it’s not deeply technical - no coding required.

Key Responsibilities

Lead and Support the Customer Support Team

● Act as the first point of contact for support agents when they have questions, need guidance, or are handling challenging cases.

● Support the team in resolving complex customer issues and step in on client calls when needed.

● Manage escalations from the support team, and coordinate with product or development teams when issues cannot be resolved within support.

● Maintain a collaborative, transparent, and customer-first team culture.

Drive AI Support Implementation and Improvement

● Take ownership of improving the use of AI within the customer support process.

● Analyze AI conversations to identify gaps, incorrect responses, missed opportunities, and areas for improvement.

● Work on increasing the number of successful AI-handled conversations while maintaining high customer satisfaction.

● Identify repetitive support issues that can be automated or improved through AI.

● Create, test, and refine AI workflows, prompts, knowledge base content, and support processes.

● Monitor AI performance and recommend changes to improve accuracy, efficiency, and resolution quality.

● Partner with relevant teams to ensure the AI support tool is continuously updated with accurate product, process, and customer information.

Build Processes and Structure

● Keep internal tools, boards, queues, and platforms organized.

● Create, improve, and document internal workflows for both AI-assisted and human-led support.

● Develop clear escalation processes between AI, human agents, the Team Lead, and product/development teams.

● Ensure the support team has the tools, resources, and documentation needed to work effectively.

● Build client-facing and internal processes that improve response times, quality, and consistency.

Develop and Coach the Team

● Provide ongoing training, coaching, and feedback to customer support agents.

● Train agents on how to work effectively with AI support tools, including when to rely on AI, when to intervene, and how to handle escalations.

● Share knowledge and create documentation that reduces repeated questions and unnecessary escalations.

● Help the team adapt to AI-driven support processes while maintaining a strong human customer experience.

Drive Performance and Continuous Improvement

● Take ownership of support KPIs through process improvements, AI optimization, and team coaching.

● Monitor support metrics such as response time, resolution time, escalation rate, customer satisfaction, AI containment rate, and ticket quality.

● Identify trends in customer issues and recommend improvements to support processes, product experience, or AI workflows.

● Partner with cross-functional teams to address recurring issues that affect customer experience.

● Lead continuous improvement initiatives within the support department.

Day-to-Day Responsibilities

● Review support tickets, GitHub tickets, and escalations.

● Monitor and maintain a clean Pending CS queue.

● Handle escalated tickets directly when needed.

● Review AI-handled conversations and identify improvements.

● Analyze failed or low-quality AI conversations and recommend fixes.

● Update or request updates to AI knowledge base content, workflows, and support documentation.

● Flag angry clients, urgent issues, or recurring customer concerns.

● Conduct weekly team meetings.

● Monitor team productivity and quality.

● Delegate channel communication to the on-shift agent when appropriate.

● Lead one internal improvement project at a time.

● Support client communication and calls when needed.

● Coordinate with product/development teams for unresolved technical issues

Required Skills and Experience

● Experience in customer support, customer success, or a similar client-facing role. While at the same time experience as an AI implentor for chatbot.

● Previous experience leading or coaching a team.

● Strong understanding of support operations, ticket management, escalations, and customer communication.

● Ability to analyze conversations, identify patterns, and improve workflows.

● Comfortable working with AI tools, automation, or support technology.

● Strong problem-solving and decision-making skills.

● Excellent written and verbal communication skills.

● Highly organized and able to manage multiple priorities.

● Process-driven mindset with a focus on continuous improvement.

● Ability to collaborate with product, development, and operations teams.

Nice to Have

● Experience implementing or managing AI-powered support tools.

● Experience working with chatbots, AI agents, automation tools, or knowledge base systems.

● Experience with GitHub, ticketing systems, support platforms, or internal workflow tools.

● Experience creating support documentation, SOPs, training materials, or process maps.

● Background in SaaS, tech support, or product support.

Ideal Candidate Profile

The ideal candidate is a hands-on support leader who enjoys solving problems, improving processes, and helping both people and systems perform better. They are comfortable managing a human support team while also taking ownership of AI support improvements.

They should be analytical, organized, proactive, and excited about using AI to make customer support faster, smarter, and more scalable without losing the quality of human customer care.