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Coursera is looking for an AI Bot Strategist to join our Scaled Support Operations team under the Services org. The Services team is made up of four sub-teams: Scaled Support, Enterprise Services, Platform Services, and the Service Operations Center. We help educators, administrators, and learners succeed by implementing innovative systems and processes that solve problems. We also develop best practices and technical expertise to enable our partners to create high-quality content. As strong advocates for the Coursera community, we work to align cross-functional teams and build scalable solutions to continuously improve the Coursera experience. As an AI Bot Strategist and the owner of our AI-driven bot ecosystem (chat + email), you will build, enhance and expand our bots ability to address and resolve our users’ needs. Additionally, you will partner with Product Managers, Engineering Managers and Business Enterprise Solutions teams to enable APIs, expand access, and create smoother hand-offs to escalation paths. You will work closely with our Content Strategist and Support Strategist to ensure the bots provide accurate information and quality interactions.
Job Responsibility:
Expand and maintain LLM-powered gen actions
convert high-impact hand-written intents to LLM-powered flows
Improve model prediction accuracy and reduce unknown predictions through training, hierarchy tuning, and experiments
Design, document, and iterate global/local bot instructions aligned with brand voice and escalation logic
Build a monitoring and testing cadence (LLM-assisted audits, manual reviews, dashboards) to track CSAT, deflection, resolution, automation, and other relevant metrics
Partner with help content optimization to ensure LLM-friendly formatting and closure of knowledge gaps
Collaborate cross-functionally (Support Ops, Engineering, Product, Vendor CSMs) on experiments, expansion of supported languages, and API integrations
Requirements:
3+ years experience building/optimizing customer support bots or virtual agents in production
Experience with LLM-powered bots (prompt/instruction design, RAG/gen actions) and hybrid ML + LLM models
Experience improving bot KPIs (deflection, CSAT, resolution) using data-driven iteration
Hands-on experience with at least one bot/vendor platform (e.g., Ada, Boost, Dialogflow, Salesforce)
Experience instrumenting/monitoring bot performance (e.g., Looker/Tableau, SQL or similar)
Nice to have:
Experience with Ada and/or Boost
API-based actioning
A/B testing and experiments
logical flows (e.g., IF statements)
Strong prompt engineering and instruction tuning for support scenarios
Familiarity with help center/knowledge base optimization for LLM consumption (structure, chunking, metadata)
Experience with model evaluation frameworks and automated LLM testing tools
Experience in online education or similar consumer support environments
Experience addressing different end user groups such as administrators, partners, consumers
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