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.
• Robust 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.

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