AI Engineer

Key Responsibilities AI & Machine Learning Development Design, develop, and deploy AI/ML models for business use cases. Build and optimize machine learning pipelines from data preparation to model deployment. Develop predictive, classification, recommendation, and NLP solutions. Fine-tune and evaluate foundation models and LLMs. Generative AI Solutions Design and implement Generative AI applications using LLMs. Develop Retrieval-Augmented Generation (RAG) solutions. Create prompt engineering frameworks and reusable AI workflows. Integrate AI copilots, chatbots, and virtual assistants into enterprise platforms. Implement AI governance, monitoring, and responsible AI practices. Data Engineering & Integration Collaborate with Data Engineers and Data Scientists to prepare training datasets. Develop APIs and microservices for AI model consumption. Integrate AI services with enterprise systems and cloud platforms. Model Deployment & Monitoring Deploy AI solutions using MLOps best practices. Monitor model performance, accuracy, drift, and reliability. Ensure scalability, security, and compliance requirements are met. Required Technical Skills AI / ML Technologies Machine Learning Algorithms Deep Learning Natural Language Processing (NLP) Generative AI Large Language Models (LLMs) Prompt Engineering Vector Databases Programming Languages Python (Mandatory) SQL Optional: Java, JavaScript, or Scala AI Frameworks & Libraries TensorFlow PyTorch Scikit-learn LangChain LlamaIndex Hugging Face Transformers OpenAI APIs / Azure OpenAI Vector Databases Pinecone Weaviate ChromaDB FAISS Cloud & MLOps Azure AI Services / Azure OpenAI AWS Bedrock / SageMaker Google Vertex AI MLflow Docker Kubernetes CI/CD Pipelines Database Technologies SQL Server PostgreSQL MongoDB Cosmos DB Leadership & Soft Skills Strong analytical and problem-solving skills. Excellent communication and stakeholder management. Ability to translate business problems into AI-driven solutions. Experience working in Agile/Scrum environments. Strong collaboration with cross-functional teams. Preferred Qualifications Experience building enterprise AI assistants and chatbots. Hands-on experience with RAG architectures and vector search. Knowledge of Responsible AI, AI Safety, and AI Governance. Exposure to Agentic AI frameworks and autonomous AI workflows. Experience with Retail, E-commerce, BFSI, Healthcare, or Supply Chain domains. Educational Qualification Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Preferred Certifications Microsoft Azure AI Engineer Associate (AI-102) Microsoft Azure Data Scientist Associate (DP-100) AWS Machine Learning Specialty Google Professional Machine Learning Engineer TensorFlow Developer Certificate Key Competencies Artificial Intelligence Generative AI Machine Learning Prompt Engineering LLM Development NLP RAG Architecture MLOps Data Analytics Innovation & Problem Solving