Artificial Intelligence Engineer

Senior AI Engineer Location: Ahmedabad, Gujarat Employment Type: Full-Time Experience: 3–7 Years Department: AI & Machine Learning Role Overview We are looking for a Senior AI Engineer with expertise in Generative AI, Agentic AI, LLMs, and RAG architectures, complemented by a solid foundation in traditional machine learning. You will build, evaluate, and deploy production-grade AI solutions with a strong focus on reliability, scalability, and code quality. Key Responsibilities - Design and develop Generative AI applications using LLMs, prompt engineering, and structured outputs. - Build advanced RAG pipelines using embeddings, hybrid search, reranking, and vector databases. - Develop AI agents and workflows using LangGraph, LangChain, tool calling, and MCP where appropriate. - Develop and deploy enterprise level applications using Azure AI services. - Implement AI evaluation frameworks, automated regression testing, and quality metrics to assess accuracy, relevance, faithfulness, and task completion. - Apply traditional ML techniques for classification, regression, predictive analytics, and NLP where required. - Build data preprocessing, feature engineering, model training, and evaluation pipelines. - Write clean, modular, testable, and maintainable Python code following software engineering best practices. - Integrate AI solutions into production systems through APIs, with appropriate security, monitoring, and observability. - Deploy and optimize AI applications on AWS, Azure, or GCP. - Collaborate with cross-functional teams, contribute to architecture decisions, and mentor junior engineers. Required Skills & Qualifications - Bachelor's or Master's degree in Computer Science, AI/ML, or a related field. - 4–7 years of experience in AI/ML development and software engineering. - Strong Python programming skills and experience with PyTorch, TensorFlow, or scikit-learn. - Understanding of machine learning fundamentals, including classification, regression, model evaluation, and feature engineering. - Hands-on experience with LLMs, Generative AI, RAG, embeddings, and vector databases. - Experience with LangChain, LangGraph, or equivalent LLM orchestration frameworks. - Understanding of AI agents, tool calling, workflow orchestration, and failure handling. - Familiarity with evaluation frameworks such as RAGAS, DeepEval, or equivalent tools. - Experience with APIs, automated testing, Git, CI/CD, databases, and cloud deployments. - Knowledge of production monitoring, debugging, security, and performance optimization. Preferred Qualifications - Experience with MCP, GraphRAG, multi-agent systems, and advanced retrieval techniques. - Knowledge of LLM fine-tuning, LoRA/PEFT, and model optimization. - Familiarity with Langfuse, LangSmith, Arize Phoenix, MLflow, Docker, and Kubernetes. - Exposure to computer vision, multimodal AI, and MLOps/LLMOps practices.