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 solid 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.

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