AI Engineer

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: Strong 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