AI Engineer / Generative AI Engineer

Job Summary

We are seeking an experienced AI Engineer / Generative AI Engineer to design, develop, and deploy scalable AI and Generative AI solutions. The ideal candidate will have strong hands-on experience with Python, Machine Learning, Large Language Models (LLMs), RAG, AI Agents, vector databases, cloud AI platforms, and MLOps.

The candidate will work closely with software engineering, data, product, and business teams to build production-ready AI solutions that solve complex enterprise business problems.

Key Responsibilities

• Design, develop, test, and deploy AI/ML and Generative AI applications.
• Build enterprise applications using LLMs, OpenAI, Azure OpenAI, Anthropic, or other foundation models.
• Develop Retrieval-Augmented Generation (RAG) solutions using embeddings, semantic search, and vector databases.
• Build and integrate AI agents and agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, or similar technologies.
• Develop prompt engineering strategies and optimize LLM responses for accuracy, relevance, and reliability.
• Build backend services and APIs using Python, FastAPI, Flask, or equivalent frameworks.
• Integrate AI models with enterprise applications, databases, APIs, and cloud services.
• Work with structured and unstructured data including documents, PDFs, text, and enterprise knowledge repositories.
• Develop solutions for document intelligence, summarization, classification, information extraction, conversational AI, and intelligent automation.
• Implement LLM evaluation techniques to measure accuracy, relevance, latency, and hallucination rates.
• Design mechanisms for guardrails, security, responsible AI, and data protection.
• Deploy and operate AI applications in cloud environments such as Azure, AWS, or Google Cloud Platform.
• Build CI/CD pipelines and automated deployment processes for AI applications.
• Monitor AI applications, model performance, data quality, latency, and infrastructure utilization.
• Optimize AI solutions for scalability, performance, reliability, and cloud cost.
• Collaborate with cross-functional teams to convert business requirements into AI-powered solutions.
• Stay current with emerging technologies in Generative AI, Agentic AI, LLMs, multimodal AI, and AI engineering.