Description
About the Company:
Netomi is the leading agentic AI platform for enterprise customer experience. We work with the largest global brands like Delta Airlines, MetLife, MGM, United, and others to enable agentic automation at scale across the entire customer journey. Our no-code platform delivers the fastest time to market, lowest total cost of ownership, and simple, scalable management of AI agents for any CX use case. Backed by WndrCo, Y Combinator, and Index Ventures, we help enterprises drive efficiency, lower costs, and deliver higher quality customer experiences.
Want to be part of the AI revolution and transform how the world’s largest global brands do business? Join us!
About the Role
We are looking for a Manager – AI Performance & Analytics to lead a team responsible for analyzing conversational AI performance and driving continuous improvements to Netomi’s AI platform.
This role sits at the intersection of data analytics, conversational AI, and LLM evaluation. The team analyzes customer conversations at scale, identifies quality gaps and automation opportunities, and partners with AI and product teams to improve model performance.
You will help define how we measure and improve the performance of AI systems that power customer support automation across millions of interactions.
Responsibilities
AI Performance Analytics
Analyze large volumes of chatbot and AI conversation data to identify performance gaps and improvement opportunities.
Define and track key AI performance metrics such as resolution rate, containment rate, response quality, and customer satisfaction.
Build dashboards and reporting frameworks using SQL, Python, and BI tools such as Tableau.
LLM Evaluation & Quality Insights
Design frameworks to evaluate the response quality of LLM responses across dimensions such as:
factuality and groundedness
Relevance to user intent
Instruction Adherence
tone and customer experience
safety and compliance
Build scalable processes for LLM-based automated evaluation and human review workflows.
Identify systematic failure patterns in AI responses and recommend improvements.
Model Improvement & Experimentation
Partner with AI and engineering teams to evaluate model upgrades, prompt changes, and new AI capabilities.
Design and analyze experiments to measure the impact of model improvements.
Generate insights that inform model training data, prompts, and product features.
Conversational Insights
Identify trends in customer interactions to uncover:
new AI automation opportunities
gaps in intent coverage
common customer pain points
Translate analytics insights into actionable recommendations for product and AI teams.
Team Leadership
Lead and mentor a team of data analysts focused on AI performance and conversational analytics.
Establish best practices for analytics, experimentation, and AI evaluation.
Collaborate closely with product, AI research, engineering, and customer success teams.
Requirements
Experience
7–10 years of experience in data analytics, data science, or AI analytics.
Experience managing or mentoring analytics teams.
Experience analyzing conversational data, customer support data, or AI-driven products is a strong plus.
Technical Skills
Strong SQL and data analysis skills.
Experience with BI tools such as Tableau or similar platforms.
Experience using Python for data analysis or experimentation.
Familiarity with machine learning or large language models (LLMs).
Preferred Experience
Experience evaluating AI or machine learning model performance.
Experience working with conversational AI platforms or chatbots.
Experience with experimentation frameworks and A/B testing.
Netomi is an equal opportunity employer committed to diversity in the workplace. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, disability, veteran status, and other protected characteristics.
Company
Netomi provides an enterprise AI platform that builds autonomous AI agents with real-time assistance and policy-driven guardrails to deliver fast, accurate, compliant customer experiences across communication channels. It emphasizes real-world reliability, transparency, and human-in-the-loop capabilities for support and transactions.
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