GEN AI Engineer

Job Summary We are looking for a skilled Generative AI Engineer to design, develop, and deploy AI-powered applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and modern AI frameworks. The ideal candidate should have hands-on experience in building enterprise-grade Generative AI solutions and integrating them into business applications. Key Responsibilities Design and develop Generative AI solutions using Large Language Models (LLMs). Build AI-powered chatbots, virtual assistants, knowledge assistants, and document intelligence solutions. Design and implement RAG (Retrieval-Augmented Generation) architectures. Develop AI Agents and multi-agent workflows for enterprise use cases. Integrate AI solutions with enterprise systems, APIs, and cloud services. Fine-tune, evaluate, and optimize foundation models for business requirements. Implement prompt engineering techniques to improve response quality and accuracy. Work with vector databases and semantic search solutions. Monitor model performance, latency, security, and scalability. Collaborate with data scientists, architects, developers, and business stakeholders. Ensure compliance with Responsible AI, security, and governance standards. Required Skills Programming Strong proficiency in: Python SQL REST APIs Git Generative AI & LLMs Hands-on experience with: OpenAI GPT Models Azure OpenAI Anthropic Claude Google Gemini Llama Models Mistral Models Strong understanding of: Prompt Engineering Fine-Tuning Embeddings LLM Evaluation Token Management AI Frameworks Experience with: LangChain LangGraph LlamaIndex Semantic Kernel CrewAI AutoGen RAG & Vector Databases Experience building: RAG-Based Applications Knowledge Search Platforms Enterprise Copilots Hands-on experience with: Pinecone ChromaDB Weaviate FAISS Azure AI Search Cloud Technologies Experience with: Microsoft Azure AWS Google Cloud Platform (GCP) Exposure to: Azure AI Services Azure Machine Learning Azure OpenAI Service AWS Bedrock Vertex AI Data & Integration Experience with: Data Pipelines ETL Processes Structured and Unstructured Data Processing API Integrations Enterprise Data Platforms Preferred Skills Experience with Machine Learning and Deep Learning concepts. Knowledge of MLOps tools such as MLflow, Kubeflow, or Azure ML. Experience with Docker, Kubernetes, and CI/CD pipelines. Understanding of AI Security, Responsible AI, and Model Governance. Exposure to multimodal AI solutions involving text, image, audio, or video models. Educational Qualification Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. Soft Skills Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities. Ability to work independently and within Agile teams. Strong collaboration and teamwork skills. Continuous learning mindset with a passion for emerging AI technologies. Nice to Have Microsoft Azure AI Engineer Associate Certification. Experience building enterprise AI assistants and copilots. Exposure to Retail, BFSI, Healthcare, Manufacturing, or E-commerce domains. Experience with Agentic AI, Multi-Agent Systems, and Autonomous Workflows. Contributions to open-source AI projects or published AI research.