AI Solutions Architect
About The Position
We’re looking for a AI Solutions Architect to drive our customer-facing chatbot and AI agent experience at Mercury. In this role, you will be pivotal in helping define the strategy for creating the optimal customer experience when interacting with AI agents. You will implement this vision through targeted configuration of workflows and automations, regular reviews of bot performance and quality coaching. You’ll sit at the intersection of customer experience, automation quality, and operational efficiency, partnering closely with Customer Support Strategy and Ops, Engineering, Product and external vendors to ensure the bot delivers a high-quality, safe, and trustworthy experience at scale. Along with the bot-focused work, you will be instrumental in defining the AI strategy within the CS org, creating best practices and supporting peers across CS in investigating AI solutions to maximise efficiency within the team.
Requirements
- 1–3 years of experience in configuration of customer-facing AI agent/chatbot (e.g., Fin by Intercom, Ada, Zendesk AI)
- 5+ years of experience in customer support backend operations or CS systems administration
- Systems thinker and problem solver, with experience in testing new solutions and change management for CS teams
- Strong technical acumen, with the ability to understand and communicate technical concepts to both technical and non-technical audiences
- Analytical thinking: ability to interpret data quickly and translate it into actionable decisions
- Cross-collaboration: works effectively with cross-functional partners across Engineering, Product, Compliance, Core Customer Support
- Stakeholder communication: delivers clear, concise updates to stakeholders at all levels
- Adaptability and a growth mindset, thriving in a fast-paced, ever-evolving environment
- Proven ability to work cross-functionally, particularly with technical teams like Engineering, Product, and Security
Nice To Haves
- An interest in software development or engineering, enabling deeper technical conversations with our engineering teams
- Experience with core customer support platforms such as Zendesk, Guru, MaestroQA/Rippit
- Proficiency in SQL and familiarity with navigating data tables
- Experience supporting remote or distributed workforce models
Responsibilities
- Strategy driver: Partner with CS and Product leadership to define the strategy and roadmap for our chatbot and email AI agents to contribute to company OKRs
- Architect and optimize AI agent workflows and procedures: Design simple, reliable conversation workflows and automations so our chatbot asks the right questions, clarifies common customer needs, and responds with accurate information, appropriately escalating to live support when needed.
- Quality reviews, analytics and bot coaching: Conduct regular reviews of bot conversations and high-level report analysis to identify trends, areas of opportunity and potential risk within the chatbot.
- Cross-collaboration to improve resolution rate and quality: Work with partners in Engineering, Product and CS Strategy and Ops to maximize the types of interactions the chatbot can support and resolve - connecting new data sources or systems on the backend to give the bot greater scope, implementing new workflows that use this data to solve new customers requests without live support intervention.
- Optimize the AI Agent experience across all channels: Expand upon the types of interactions and experiences that qualify for the email AI agent and other asynchronous channels.
- Compliance and security: Ensure Mercury’s high standards for security and compliance are woven into the foundations of our AI-assisted CS strategy
- AI vendor relationship owner: Own the relationship with AI vendors for CS solutions, including Intercom. Raising issues, requesting fixes, staying on top of product releases and coordinating changes that impact CS operations
- Scoping of internal agent co-pilot: Drive efforts to assess and implement agent assist AI tools to maximise agent efficiency
- Evaluation of AI tooling for CS partners: Support other teams, such as Learning and Development and QA in evaluating how other tools’ AI offerings can increase efficiency across CS.
Benefits
- equity (stock options)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1-10 employees
