Amazon Growth Engineer

About the role

This is a graduate program for engineers with AI/ML, data or systems skills. We will train you on Amazon, then hand you the full growth engine for million-dollar brands on Amazon India and the US.

You do not need any Amazon or e-commerce experience. We need front-runners who think in data and systems, and look for evidence before they act, and we will teach you the marketplace.

Most Amazon roles split listings, ads and inventory across three people who rarely talk. This role joins them. You will plan the sales number, build the listings and ads that deliver it, make sure stock is there to sell, and explain every gap between plan and actual.

You will work inside ProfitStory's in-house AI platform (Moneyball), with a Postgres data warehouse and agentic tools for advertising and seller analytics. ProfitStory manages around $60M in client GMV and is part of NVIDIA Inception. Your engineering skills are the advantage here: you will build the models, automations and guardrails that let you manage brands at a scale no manual team can match.

What you'll own

We cross-train you across seven areas, one at a time. Within your first year you own all seven for your brands, with one outcome: the brand hits its sales plan profitably, with no surprises.

1. Listings - SEO and AEO

• Write and optimise titles, bullets, descriptions, A+ content and backend keywords using AI tools, grounded in Brand Analytics and search query data.
• Optimise for answer engines too (AEO): Amazon Rufus, and AI shopping answers on ChatGPT, Perplexity and Google. Structure content so these engines can find, understand and recommend the product.
• Track indexing, keyword rank and conversion rate after every change.

2. Inventory planning

• Build replenishment plans in SQL and AI tools: sell-through, days of cover, lead times, MOQ and FBA capacity limits.
• Plan inbound shipments to avoid stock-outs and excess or aged inventory, ahead of sales events.

3. PPC - plan and execute

• Build and run Sponsored Products, Brands and Display campaigns end to end: structure, keywords, bids, budgets and negatives.
• Manage ACoS, TACoS and ROAS targets set against the brand's profit goals, not just spend.

4. Evidence, guardrails and validation

• Set the rules every change must pass before it goes live: bid and budget caps, price floors, listing edits, reorder quantities.
• Validate every AI recommendation before it is executed: it must cite the data behind it, and that evidence must hold up when you check it. After execution, measure the outcome against what was expected. Catch anomalies in spend, price, Buy Box and stock early.

5. Automation

• Turn repeated work into scripts, SQL jobs, alerts and AI agents: reports, bid rules, stock alerts, listing checks.
• Document each automation so the team can run and trust it.

6. Forecasting and the sales plan

• Forecast monthly sales by ASIN from history, seasonality, events (Prime Day, Great Indian Festival, BFCM) and planned ad spend.
• Turn the forecast into a plan the brand signs off: revenue, units, ad spend and inventory needed.

7. Deviation analysis

• Every week, compare actual against plan and find the cause: traffic, conversion, price, ad spend, stock-outs, Buy Box loss or competitors.
• Present the fix and the revised plan to the client in clear, simple language.

What you bring

The critical skill is analytics. You find patterns, correlations and causes in data, and you separate signal from noise. When AI recommends an action, you check its citations, test it against the evidence, decide if it is safe to execute, and measure the result afterwards.

• B.E. / B.Tech / M.Tech in any branch, 2027 final-year students, with a strong foundation in one of:

- AI/ML: Model building, LLMs, prompt engineering, RAG or agents.

- Data: SQL, statistics, data analysis, time-series or forecasting.

- Systems: Python, APIs, automation, backend or data pipelines.

• Working SQL and Python. You can query a dataset and explain what it says.
• Hands-on use of AI tools (Claude, ChatGPT, Gemini or similar) in projects or daily work. Show us what you built.
• A project, internship or GitHub repo that shows how you solve problems with data or code.
• Curiosity about business: how products are sold, priced and found by customers.
• Clear communication in English. You can explain a number to a non-technical person.
• Willingness to learn fast, take ownership, and work extra hours during peak sales events.

No Amazon or e-commerce experience needed. We teach that.

Nice to have

• Kaggle, hackathon or competition work in ML, forecasting or analytics.
• Experience with any REST API, or with building an AI agent or chatbot.
• Familiarity with Excel or Google Sheets for quick analysis.
• Exposure to BI tools such as Metabase, Looker Studio or Power BI.
• Your own experience selling online, on any platform.

Why join

• Use your AI and data skills on real money from day one: million-dollar brands on Amazon India and the US.
• Learn a rare mix: engineering plus marketplace business, which few graduates have.
• Work with new-age AI tools every day, and build your own on our platform.
• Grow with a team in NVIDIA Inception, building the future of marketplace growth.

Details

• Eligibility: B.E. / B.Tech / M.Tech / Msc / MCA, any branch (2027 final-year students only)
• Location: Coimbatore, on-site
• Type: Internship, with conversion to a full-time role based on performance.
• Compensation: Based on market standards, performance in interviews and strength of candidate