Requirements
- Core

Experience:
2+ years in AI Engineering, NLP, or applied Machine Learning, with a track record of deploying production-grade LLM applications.
- LLM & RAG Systems: Deep expertise in RAG architectures, vector databases (e.g., pgvector), hybrid search, embedding pipelines, retrieval optimization, and hallucination mitigation.
- Agentic Workflows: Practical experience designing autonomous agents, multi-step orchestration, tool-calling pipelines, grounding techniques, and structured prompt engineering.
- Backend Engineering: Solid proficiency in Java or Kotlin with Spring Boot, specializing in scalable REST API development and distributed system design.
- Azure Cloud & Data: Hands-on experience with Azure OpenAI, Azure AI services, PostgreSQL, Service Bus, and Azure Container Apps within event-driven architectures.
- Infrastructure & Security:



Solid foundation in Infrastructure as Code (Terraform), CI/CD pipelines, managed identities, Key Vault, autoscaling, and enterprise cloud security.
- LLM Ops & Observability: Proven ability to implement LLM evaluation frameworks, production telemetry, integration testing, cost governance, and real-time troubleshooting. Pay: From ₹20,000.00 per month

Benefits:
- Work from home Application Question(s):
- Have you deployed an LLM application to end-users that runs in real-time? What was the primary model and use case?

Experience:
- Ai Engineering: 2 years (Preferred) Language:
- English (Preferred) Work

Location:
Remote

📌 AI Engineer (India)
🏢 Pragati Training Services
📍 India