Emerging Account Executive (India)

About The Role & Team

Amplitude is the digital analytics platform built for the AI era. The world's best product teams use Amplitude to sense how customers and, increasingly, AI agents experience their products through Amplitude Analytics, Session Replay, and Agent Analytics, all powered by one of the world's largest behavioral datasets; decide what to ship with Statsig's experimentation and feature management; and act on those insights with Wave, our proactive product agent. You'll be selling the platform at the center of how modern digital and AI products get built, in one of the fastest-growing digital markets in the world.

Join our Sales team of Account Executives who know software sales and how to identify and win opportunities with some of the fastest growing and most influential digital product companies. We want the best of the best, and we make sure that top performers are rewarded. This role is a launchpad: you'll own a territory, run full sales cycles end to end, and grow upmarket as the segment grows.

As an Emerging Enterprise AE, you will:

• Create new opportunities in the emerging enterprise segment through prospecting, networking, etc. Primary focus is to land new logos in India.
• Become knowledgeable across the full Amplitude platform (Analytics, Session Replay, Agent Analytics, Statsig, and Wave) and conduct discovery calls and presentations to prospective customers. Attempt new sales methods through fearlessness and willingness to take risks.
• Effectively sell the value of Amplitude to key stakeholders, from product, engineering, and data leaders to business buyers, while navigating a multi-threaded sales cycle.
• Have responsibility for expanding existing customers (working with a Customer Success team) and landing new logos.
• Lead territory building initiatives in the emerging enterprise segment by working with technology partners, solutions partners, product management networking groups and regional events to drive awareness, educate the market, create net new opportunities and influence current pipeline.
• Put AI to work in your own selling (research, personalization, call prep, pipeline hygiene) the same way our customers put it to work in their products, and share what works with the team.
• Collaborate well with team members (particularly an SDR & Sales Engineer); proactively identify best practices and share feedback.
• Take quantitative and strategic approaches in territory planning. Understand total pipeline size, top opportunities, opportunity stage management, coverage factor, and historical close rate. Forecast accurately.
• Exceed quarterly and annual targets.

You'll be a great addition to the team if you have:

• 3+ years of quota-carrying SaaS sales experience, including time in a closing role
• Ability to tell a story using data
• Experience creating your own pipeline: you're a full-cycle seller, not someone who waits for leads
• Familiarity with account planning fundamentals
• A track record of top performance against quota
• Fluency with AI tools in your day-to-day workflow, and genuine curiosity about how AI is changing the way products are built, measured, and improved
• Ability to work and thrive in a highly collaborative company and team setting
• Excellent communication and presentation skills
• You are hungry, and thrive in a growing, start-up environment
• There is no challenge too big to you
• Opening up new accounts is exciting to you
• You thrive on experimentation and innovating the sales process
• You are naturally curious and empathetic towards customers and prospects
• You embrace feedback and are open to developing personally and professionally. Coachability matters more to us than a perfect résumé.

At a minimum, you need to have:

• Closing experience at the Mid-Market or Emerging Enterprise level for 3+ years
• Worked for a tech/SaaS company (preferably in the analytics, data, experimentation, or martech space)

A plus if you have:

• Experience selling into BFSI or digital-native accounts in India
• Exposure to the modern data stack (Snowflake, Databricks, AWS) or experimentation/feature-management tooling