At Airtel , we're not just scaling connectivitywe're redefining how India experiences digital services. With 400M+ customers across telecom, financial services, and entertainment, our impact is massive. But behind every experience is an opportunity to make it smarter . We're looking for a Product Manager AI to drive next-gen intelligence for our customers and business. AI is a transformational technology and we are looking or skilled product managers who will work on leveraging AI to power everything from our digital platforms to customer experience. You'll work at the intersection of machine learning, product design, and systems thinking to deliver AI-driven products that create tangible business impactfast.
Experience require : 8+ yrs
Location: Gurgaon
What You'll Do
Lead and contribute to AI-Powered Product Strategy
- Define product vision and strategy for AI-led initiatives that enhance productivity, automate decisions, and personalise user interactions across Airtel platforms.
Translate Business Problems into AI Opportunities
- Partner with operations, engineering, and data science to surface high-leverage AI use cases across workforce management, customer experience, and process automation.
Build & Scale ML-Driven Products
- Define data product requirements, work closely with ML engineers to develop models, and integrate intelligent workflows that continuously learn and adapt.
Own Product Execution End-to-End
- Drive roadmaps, lead cross-functional teams, launch MVPs, iterate based on real-world feedback, and scale solutions with measurable ROI.
What You Need to be Successful
- Influential Communication - Craft clarity from complexity. You can tailor messages for execs, engineers, and field teams aliketranslating AI into business value.
- Strategic Prioritisation - Balance business urgency with technical feasibility. You can decide what not to build, and defend those decisions with data and a narrative
- Systems Thinking - You can sees the big picture how decisions in one area ripple across the business, tech stack, and user experience.
- High Ownership & Accountability - Operate with a founder mindset. You don't wait for direction you can rally teams, removes blockers, deal with tough stakeholders and drives outcomes.
- Adaptability - You thrive in ambiguity and pivot quickly without losing sight of long-term visionkey in fast-moving digital organizations.
Skills You'll Need
AI / ML Fundamentals
- Understanding of ML model types: Supervised, unsupervised, reinforcement learning
- Common algorithms: Linear/logistic regression, decision trees, clustering, neural networks
- Model lifecycle: Training, validation, testing, tuning, deployment, monitoring
- Understanding of LLMs, transformers, diffusion models, vector search, etc.
- Familiarity with GenAI product architecture: Retrieval-Augmented Generation (RAG), prompt tuning, fine-tuning
- Awareness of real-time personalization, recommendation systems, ranking algorithms, etc
Data Fluency
- Understanding Data pipelines
- Working knowledge of SQL and Python for analysis
- Understanding of data annotation, labeling, and versioning
- Ability to define data requirements and assess data readiness
AI Product Development
- Defining ML problem scope: Classification vs. regression vs. ranking vs. generation
- Model evaluation metrics: Precision, recall, etc.
- A/B testing & online experimentation for ML-driven experiences
ML Infrastructure Awareness
Know what it takes to make things work and happen.
- Model deployment techniques: Batch vs real-time inference, APIs, model serving
- Monitoring & drift detection: How to ensure models continue performing over time
- Familiarity with ML platforms/tools: TensorFlow, PyTorch, Hugging Face, Vertex AI, SageMaker, etc. (at a product level)
- Understanding latency, cost, and resource implications of ML choices
AI Ethics & Safety
We care deeply about our customers, their privacy and compliance to regulation.
- Understand Bias and fairness in models: How to detect and mitigate them
- Explainability & transparency: Importance for user trust and regulation
- Privacy & security: Understanding implications of sensitive or PII data in AI
- Alignment and guardrails in generative AI systems
Preferred Qualifications
- Experienced Machine Learning/Artificial Intelligence PMs with 8+ yrs of working experience
- Experience building 0-1 products, scaled platforms/ecosystem products, or ecommerce
- Bachelor's degree in Computer Science, Engineering, Information Systems, Analytics, Mathematics
- Masters degree in Business
