AI Engineer
Stop calling yourself an AI Engineer.
Instead, ask yourself:
Can you build backend systems that don't break at scale?
Can you take an LLM application from a cool demo to a production-grade product?
Can you design RAG pipelines, work with vector databases, optimize latency, and handle the infrastructure challenges that come with real users?
If these are the problems you enjoy solving, we should talk.
🚀 We're hiring an engineer who can combine Backend Engineering and AI to build reliable, scalable products.
📍 Remote (India)
💰 Up to ₹1.2 Cr CTC
We're looking for experience with:
✔ Python & Backend Development
✔ LLMs & Generative AI
✔ RAG Pipelines & AI Agents
✔ Vector Databases
✔ AWS / GCP / Kubernetes
✔ Production Deployment & Scaling
This isn't a role for building demos.
It's for building AI systems that people actually use.
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💬 Interested candidates can DM or comment "AI"
#AIEngineer #Remote #GenAI #LLM #AIAgents #RAG #VectorDatabases #PythonDeveloper #BackendEngineering #SoftwareEngineering #MLOps #CloudComputing #AWS #Kubernetes #ArtificialIntelligence #RemoteJobs #HiringNow #AI
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Interview advice
Going for the Data Scientist role at Not mentioned? A few things that help freshers walk in prepared:
- Be ready to explain one model you built in plain English — the problem, why you chose that approach, and how you knew it worked.
- Prepare two or three thoughtful questions to ask them about the team, the work and growth; "I have no questions" reads as low interest.
- It is fine not to know something — say how you would find the answer. Freshers are hired for how they think, not for knowing everything already.
- Use STAR for "tell me about a time" questions — Situation, Task, Action, Result — so your story stays clear and short.
- Keep answers tight and on-point; avoid rambling or personal topics like religion, politics, relationships or family.