Shiprocket is hiring Associate Product Manager / Product Manager – Fastrr | Gurugram — Job Update | Vishal Kushwaha
Overview
Shiprocket is hiring for the role of Associate Product Manager / Product Manager for their Fastrr team in Gurugram, Haryana. This is a permanent position focused on developing AI/LLM-powered products.
Quick Snapshot
| Company | Shiprocket |
| Position | Associate Product Manager / Product Manager – Fastrr |
| Location | Gurugram, Haryana |
| Job Type | Full-time |
| Experience | 1-3 years |
Eligibility & Qualification
- 1–3 years of product experience
- At least one shipped AI/LLM-powered feature, preferably conversational AI or voice AI
Required Skills
- Hands-on understanding of conversational AI mechanics, including prompt design, context handling, fallback, and human-handoff flows
- Experience setting up AI evals and measuring output quality through accuracy, containment, or similar metrics
- Strong analytical skills with hands-on SQL experience and the ability to independently pull and analyse data
- Understanding of AI unit economics, including per-conversation costs, margin thinking, and usage-based pricing
- Excellent written communication skills with the ability to independently create clear product specs and PRDs
Key Responsibilities
- Own the end-to-end product lifecycle – from identifying the problem and defining the solution to launch, iteration, and scale
- Work closely with Engineering, Design, Data, and Business teams to build and launch AI-powered products
- Define product vision, requirements, user journeys, PRDs, user stories, and acceptance criteria
- Design and iterate on conversational and voice AI experiences, including prompts, context handling, fallbacks, and human-handoff flows
- Define and track AI quality metrics and evaluation frameworks to continuously improve model output and accuracy
- Analyse product and customer data using SQL to identify insights, opportunities, and areas for improvement
- Monitor key product metrics such as activation, adoption, engagement, containment, accuracy, and retention
- Understand and optimise AI unit economics, including per-conversation costs, usage, margins, and pricing implications
- Conduct user research and work with customer-facing teams to identify pain points and translate them into product opportunities
- Run experiments and use data-driven insights to improve product adoption and engagement
- Collaborate with engineering teams on technical feasibility, prioritisation, sprint planning, and execution
- Own product launches and measure post-launch performance to drive continuous improvement
- Stay updated on emerging AI/LLM capabilities, agentic workflows, RAG, and AI product trends and identify opportunities to apply them