We are seeking a skilled AI/ML Engineer to join our team and contribute to the design, development, and deployment of intelligent AI solutions, with a strong focus on conversational AI and Retrieval-Augmented Generation (RAG) architectures.
This role is ideal for an experienced engineer who has successfully delivered production-grade AI applications, particularly chatbots and knowledge-driven systems, while leveraging Microsoft Azure as the primary cloud platform.
Location: [Remote / Hybrid / Bengaluru / Specify as per company policy]Experience Level: Mid-Senior (8+ years total IT/engineering experience)
Key Responsibilities
Design, build, and deploy enterprise-grade chatbots and conversational AI applications using RAG architecture to enable accurate, context-aware, and hallucination-reduced responses
Develop end-to-end RAG pipelines including document ingestion, chunking, embedding generation, vector storage, hybrid/semantic retrieval, re-ranking, and generation augmentation
Integrate Large Language Models (LLMs) (via Azure OpenAI or other providers) with retrieval systems and implement advanced techniques such as query rewriting, contextual compression, and evaluation metrics
Architect and implement scalable AI/ML solutions on Microsoft Azure, leveraging services such as Azure OpenAI, Azure AI Search (for vector/hybrid search), Azure Machine Learning, Azure AI Services, Prompt Flow, and Azure Cosmos DB / Azure SQL
Build and maintain production MLOps pipelines using Azure DevOps, MLflow, or equivalent tools for model versioning, CI/CD, monitoring, and automated retraining
Collaborate with data engineers, product managers, and domain experts to translate business requirements into high-quality AI features
Optimize AI systems for performance, cost, latency, and reliability in cloud environments
Implement evaluation frameworks, A/B testing, and continuous improvement for conversational accuracy and user satisfaction
Ensure secure, compliant, and ethical AI implementations (guardrails, PII handling, content filtering)
Required Qualifications & Experience
8+ years of overall software engineering / development experience
4+ years of hands-on experience with Microsoft Azure cloud platform (Azure PaaS services preferred)
2+ years of dedicated AI/ML engineering experience, with proven delivery of production AI/ML solutions
Strong hands-on experience designing and implementing chatbots / conversational agents using RAG architecture
Practical expertise in building RAG systems, including:
Vector databases / vector search (Azure AI Search, FAISS, Pinecone, Weaviate, etc.)
Embedding models and semantic search techniques
Orchestration frameworks such as LangChain, LlamaIndex, Semantic Kernel, or Haystack
Proficiency in Python (production-grade coding)
Experience working with LLMs — prompt engineering, fine-tuning (nice to have), chaining, tool/function calling
Familiarity with Azure AI ecosystem: Azure OpenAI, Azure Machine Learning, Azure Cognitive Services / AI Search, Bot Framework (advantage)
Good understanding of MLOps practices and deployment patterns (Docker, Kubernetes, CI/CD)
Preferred / Nice-to-Have Skills
Azure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate)
Experience with agentic AI / multi-agent systems
Knowledge of classical ML + deep learning frameworks (PyTorch / TensorFlow)
Exposure to evaluation tools (RAGAS, DeepEval) and observability for GenAI applications
Previous work in enterprise environments (security, scalability, cost optimization)
What We Offer
Opportunity to work on cutting-edge Generative AI and RAG-powered solutions
Collaborative environment with focus on innovation and learning
Competitive compensation and benefits