Product Engineer (Junior) — VenXR

VenXR builds AdsGPT: brands plan, run and optimise their ad campaigns by talking to it. We're hiring a Product Engineer, one to two years in, who builds with LLMs rather than around them.

Features, end to end — from a half-formed idea to production, and you own what happens after it ships. Most of what you build will have a model in the loop: campaign planning that reasons about a brand's goals, interfaces that assemble themselves from whatever the model surfaced, agents calling real tools against real ad platforms.

Tech Stack

Frontend: React.js

Backend: Python, Django

AI: Claude and other frontier models, LangChain / LangGraph, MCP

AI-native, and we mean it literally

Fundamentals — tokens, context windows, cost, latency, structured outputs, why a confident model is often wrong

Multi-agent patterns — when splitting work across agents helps, and the commoner case where it just multiplies failure modes

Where most of the quality lives

Evaluation — knowing whether what you built works, which is harder than building it

Self-taught side projects count; One to two years shipping product

React.js, Python with Django — or FastAPI plus the obvious ability to get to Django in a fortnight.





At least one LLM-backed feature real users touched, where you owned the prompt, the orchestration and the failure modes

REST APIs, SQL or NoSQL, and enough system design to know when your approach won't survive scale

Share links to your GitHub, portfolio, or projects you've shipped. What Helps

LLM evaluation and monitoring — Ragas, LangSmith, Langfuse, or your own harness

Cloud infra, Docker, CI/CD

Explainable or compliance-aware AI in a regulated domain

Stakeholder sense — know when to pull in Product, Design or Business

High standards — hold your work to a bar nobody is checking

Disagree and commit — argue the call hard, then back it fully

Vitality — energy that holds up in month six

In practice: ship fast, test in production more than is strictly comfortable, and sit close enough to the founders that 'I'll ask Product' means turning around.

Tech screening round — 30 minutes.

Take-home — a small orchestrated LLM system. Using AI is expected; Health cover, team offsites, and a culture that's versatile in the ways that matter rather than the ways that photograph well.

Skills: mcp,django,react.js,langgraph,system design,sql,orchestration,langchain,docker

📌 JR Design engineer (Pune)
🏢 Venxr
📍 Pune