Artificial Intelligence Engineer

Job Description & Summary:

IFS II Senior AI Engineer II PAN India

We are seeking a Senior AI Engineer/Architect with deep technical expertise in architecting and building resilient, production-grade AI applications using modern GenAI frameworks and Retrieval-Augmented Generation (RAG) techniques. This role demands hands-on expertise in Python, LangChain ecosystem (LangFlow, LangGraph, LangFuse), and Vector Databases such as Azure AI Search, Qdrant, and the likes. The ideal candidate should be capable of architecting intelligent, highly performant AI agent-based systems that combine LLMs with semantic search, tool orchestration, and business logic.

Responsibilities:

• Design, develop and deploy LLM-powered intelligent agents and RAG-based applications using frameworks like LangChain, LangFlow, and LangGraph.
• Implement LangFuse for observability, latency tracking, and hallucination detection in GenAI pipelines.
• Build scalable semantic search pipelines using vector databases such as Qdrant, Pinecone, Azure AI Search, and integrate with LLM-driven workflows.
• Develop Python-based microservices for embedding AI capabilities into enterprise-grade platforms using frameworks such as FastAPI, FastMCP, Flask, or Django.
• Leverage OpenAI, Gemini, Claude, or open-source LLMs (e.g., LLaMA, PaLM, Mistral) via APIs or self-hosted models for multi-turn conversations and knowledge-driven tasks.
• Construct multi-hop reasoning, tool-calling agents capable of real-world decision-making across domains like customer support, marketing, and operations.
• Automate deployment of AI solutions, using Azure DevOps or GitHub Enterprise and GitHub Actions.
• Effectively collaborate with data engineers, AI developers and product teams to review existing AI Solutions architecture and identify technical alternatives to improve non-functional capabilities of existing solutions.
• Align GenAI solutions with business use cases and ensure robust delivery pipelines.
• Define and implement in-house evaluation metrics for latency, grounding, factual consistency, and user engagement.

Mandatory skill sets:

• Proficiency in Python with a strong understanding of data structures, concurrency, and REST API development and deployments on Serverless environments on Microsoft Azure.
• Extensive, hands-on experience with GenAI tools: Predominantly,
• LangChain (Agents, Chains, Callbacks, Tools),
• LangFlow (Visual orchestration of agent workflows),
• LangGraph (Stateful graph-based agent routing),
• LangFuse (Monitoring & Evaluation).
• Proven experience with RAG-based system design, including chunking, embedding generation, retrieval strategies (dense, hybrid), and feedback loops.
• Exposure to Azure AI Services like AI Search (formerly Cognitive Search), Document Intelligence.
• Exposure to Microservices-oriented and Containerized deployment architecture leveraging Azure Kubernetes Services (AKS)
• Hands-on with Vector Stores: Qdrant, Azure AI Search, Pinecone, Chroma, Weaviate.
• Solid understanding of Embedding Models, Chat
• Completion Models, LLM token limits, context windowing, and semantic similarity techniques.
• Knowledge of OpenAI API, LiteLLM, Hugging Face Transformers, and LLM fine-tuning & evaluation.
• Extensive experience building and deploying LLM solutions in cloud environments like Azure.
• Exposure to observability tooling and latency optimization strategies in GenAI pipelines.
• Experience in prompt engineering, context synthesis, and few-shot learning patterns.
• Working knowledge of CI/CD pipelines to deploy AI solutions, using Azure DevOps or GitHub Enterprise and GitHub Actions.

Preferred skill sets:

Azure Devops, AI

Years of experience required:

3+ yrs

Education qualification:

Any Ug/Pg