Paytmpayments8h ago

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Campaign Manager - AI Operations

India·NoidaFull-time Employmentmid

MarketingCampaign Manager

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Quick Summary

Key Responsibilities

AI Agent Creation: Build and configure AI voice agents for different merchant use cases by defining conversation journeys, agent behavior, business rules, objection handling, and closure logic.

Requirements Summary

Own AI campaigns end-to-end, from understanding the business requirement and creating the AI agent to testing, launch, monitoring, and post-live optimization.

Technical Tools

MarketingCampaign Manager

About Us:

Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology.

About the team:

The AI Operations team is responsible for building, launching, and scaling AI-powered voice and Agentic AI solutions across Paytm’s merchant ecosystem.

The team works closely with Business, Product, Technology, Data, QA, and Operations teams to drive AI-led automation across merchant engagement, retention, activation, support, and service journeys.

The team owns the complete operational lifecycle of AI campaigns — from use-case identification and conversational journey design to voice-bot creation, prompt development, testing, deployment, performance monitoring, and continuous optimization.

About the role:

We are looking for a Campaign Manager – AI Operations who will own the end-to-end execution and success of AI-powered voice and Agentic AI campaigns.

The role will involve creating AI voice agents, writing and optimizing prompts, designing conversational journeys, launching campaigns, monitoring performance, analyzing AI interactions, and continuously improving the agent to drive measurable business outcomes.

The candidate should have a strong combination of operations understanding, prompt engineering, conversational AI, analytical thinking, and execution skills.

Role Expectations/ Responsibilities:

AI Agent Creation: Build and configure AI voice agents for different merchant use cases by defining conversation journeys, agent behavior, business rules, objection handling, and closure logic.

Prompt Engineering: Write, test, and continuously optimize production-ready prompts to ensure the AI agent follows the required conversation flow, understands merchant responses, asks relevant questions, handles objections, and drives the intended outcome.

Conversational Journey Design: Translate business requirements and operational processes into structured AI conversations covering opening, intent identification, probing, resolution, objection handling, confirmation, and closure.

Campaign Ownership: Own AI campaigns end-to-end, from understanding the business requirement and creating the AI agent to testing, launch, monitoring, and post-live optimization.

Campaign Performance: Track and analyze campaign KPIs such as connect rate, successful outcome, retention, activation, conversion, AHT, FCR, drop-offs, retry effectiveness, and cost per successful outcome.

AI Call Analysis: Review AI call recordings and transcripts to identify issues such as incorrect responses, repetition, hallucination, unnecessary probing, long monologues, missed objections, incorrect intent identification, and poor call closure.

Prompt & Agent Optimization: Convert call-level observations into actionable improvements in prompts, agent instructions, conversation flows, business logic, and tool usage.

Agentic AI Optimization: Work on improving the agent's ability to understand context, make appropriate decisions, use available tools, follow business rules, and complete the intended merchant journey autonomously.

Quality Management: Partner with QA teams to define AI quality parameters, conduct regular audits, identify critical quality/compliance gaps, and implement corrective actions.

Business Outcome Management: Ensure AI campaigns are optimized for measurable business outcomes and not only operational metrics such as call connectivity.

A/B Testing & Experimentation: Design and execute experiments across prompts, conversation flows, scripts, retry strategies, and campaign configurations to improve campaign performance.

Production Monitoring: Closely monitor newly launched campaigns, identify issues early, and drive corrective actions to stabilize and scale campaigns.

Data & Analytics: Analyze campaign dashboards, call-level data, MIS, and AI performance trends to identify gaps and opportunities for improvement.

Cross-Functional Collaboration: Work closely with Product, Engineering, Data, QA, Business, and Operations teams to develop, launch, troubleshoot, and scale AI campaigns.

AI Platform Coordination: Coordinate with the internal Agentic AI/Product/Technology teams for platform enhancements, integrations, tool/API requirements, defects, and new capabilities required for campaigns.

Process Automation: Identify opportunities to automate campaign setup, reporting, ticket updates, retries, outcome capture, and other operational processes.

Cost Optimization: Monitor AI calling efficiency and optimize call duration, retry strategy, conversation flow, and campaign configuration to improve cost per successful outcome.

Documentation & Governance: Maintain campaign documentation including prompts, conversation flows, business rules, test cases, success metrics, changes, and deployment requirements.

Key Success Metrics:

The role will be measured across AI quality, campaign performance, business outcomes, and operational efficiency, including:

AI campaign connect rateSuccessful outcome / conversion rate

Merchant retention and activation AI conversation quality score

AHT and call efficiency FCR / successful resolution

Prompt and AI agent performance improvement

Reduction in hallucinations and critical compliance issues

Retry effectiveness

Cost per successful outcome

Campaign launch timelines

Automation and manual effort reduction

Required Qualifications:

Experience: 1–1.5 years of experience in Operations, Campaign Management, Contact Centre Operations, Conversational AI, Voice Automation, or a related domain. (Freshers can also apply).

AI/ Voice Experience: Hands-on experience with AI voice bots, Agentic AI, conversational AI, IVR, voice automation, or contact-center automation.

Prompt Engineering: Strong hands-on experience in writing and optimizing prompts for AI/LLM-based applications, preferably voice-based systems.

Operations Understanding: Strong understanding of contact-center operations, customer/merchant journeys, campaign management, and operational KPIs.

Conversation Design: Ability to convert complex business requirements into simple, structured, and effective AI conversations.

Analytical Skills: Strong analytical and problem-solving skills with proficiency in Excel/Google Sheets. SQL and BI tools will be an advantage.

AI Quality: Ability to analyze AI conversations and identify issues related to intent understanding, prompt adherence, hallucination, repetition, tone, compliance, and outcome achievement.

Stakeholder Management: Ability to work with Product, Engineering, Data, QA, Business, and Operations teams to drive AI initiatives.

Execution: Strong ownership and ability to manage multiple AI campaigns simultaneously from requirement gathering through production and optimization.

Communication: Excellent written and verbal communication skills with strong documentation capabilities.

Preferred Skills:

Experience in FinTech, E-commerce, Payments, B2B, Merchant Operations, or Contact Centre Operations.

Hands-on experience with Agentic AI / LLM-based applications.

Experience building or managing AI voice agents / OBD / IVR journeys.

Understanding of LLMs, speech-to-text, text-to-speech, intent classification, tool calling, APIs, and agent workflows.

Exposure to CRM/ticketing systems and workflow automation.

Experience with SQL, dashboards, analytics, and experimentation.

Strong understanding of conversational design and voice-bot best practices.