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▷ [15h Left] AI Product Manager - Sales & Marketing

▷ [15h Left] AI Product Manager - Sales & Marketing

Dr. Reddy's LaboratoriesIndia
4 hours ago
Job description

Job Summary

We are hiring a Technical AI Product Manager to lead the design and delivery of AI and Gen AI products for sales and marketing domains. You will work across product, ML, and engineering teams to build scalable, production-grade AI systems. This role demands deep technical fluency, structured product thinking, and execution ownership from roadmap to deployment.

Roles and Responsibilities

  • Own product lifecycle from problem framing to deployment and iteration
  • Define clear specs with data science and engineering for ML and GenAI solutions
  • Lead development of RAG pipelines, prompt orchestration, fine-tuning, and evaluation workflows
  • Balance model performance, latency, cost, scalability, and compliance constraints
  • Design API-first, modular, secure product architectures
  • Monitor product KPIs and drive iterative improvements
  • Prioritize across exploratory and scalable use cases
  • Stay current with AI / LLM tech and translate into product capabilities

Skills Required

Functional

  • Strong ownership with ability to structure ambiguous technical problems
  • Deep understanding of commercial workflows like rep coaching using call summaries, GenAI-driven campaign asset creation, next-best-action models, and AI-guided segmentation
  • Experience aligning AI product success metrics with business KPIs such as conversion uplift, rep productivity, and content reuse rates
  • Skilled at navigating trade-offs between explainability, performance, and cost in commercial AI applications
  • Proven delivery of AI products in real-world GTM or sales enablement environments
  • Technical

  • 8+ years of experience in AI & Analytics for sales and marketing functions
  • Deep knowledge of LLMs, embeddings, vector stores, and RAG architectures
  • Hands-on with LangChain, Pinecone, OpenAI, Azure AI, Vertex AI or similar
  • Proficient in evaluating model metrics like top-k accuracy, latency, precision, recall
  • Comfortable reviewing code, writing specs, and using Git, Postman, Jupyter
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