AI Engineer - Generative AI, LLM & RAG

Build practical AI and Generative AI solutions that address real-world business problems, from prototype through production. This mid-level role focuses on developing scalable AI applications, integrating Large Language Models, building RAG-based solutions, and bringing AI capabilities into enterprise platforms., * Develop and implement AI/ML solutions using Python and modern AI/ML frameworks.

• Build Generative AI applications using Large Language Models (LLMs).
• Develop RAG-based applications using document processing, embeddings, vector databases, and semantic search.
• Integrate LLMs such as Azure OpenAI, OpenAI, AWS Bedrock, Google Gemini, or equivalent platforms.
• Develop AI-powered chatbots, virtual assistants, document summarization, classification, extraction, and knowledge-management solutions.
• Implement prompt engineering techniques and evaluate LLM responses for accuracy, relevance, and reliability.
• Build and integrate REST APIs and microservices to expose AI capabilities to enterprise applications.
• Work with structured and unstructured data and develop data-preparation and processing pipelines.
• Implement AI solutions using cloud services on Azure, AWS, or Google Cloud.
• Collaborate with senior engineers and architects to develop scalable and production-ready solutions.
• Participate in proof-of-concepts and rapidly evaluate emerging AI technologies.
• Develop unit tests, integration tests, and automated validation for AI applications.
• Monitor AI applications and troubleshoot performance, accuracy, and production issues.
• Follow enterprise standards for security, data privacy, responsible AI, and application development.
• Contribute to technical documentation, solution design, and knowledge-sharing activities.

• 3-6 years of experience in software engineering, AI/ML, data science, or a related technology field.
• Strong hands-on programming experience with Python.
• Experience with Machine Learning and/or Generative AI applications.
• Practical experience working with LLMs and prompt engineering.
• Experience building RAG applications using embeddings and vector search.
• Knowledge of ML/AI frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Experience working with REST APIs and microservices.
• Experience with SQL and relational or NoSQL databases.
• Experience with at least one cloud platform: Azure, AWS, or Google Cloud.
• Familiarity with Git and CI/CD practices.
• Good understanding of software development lifecycle and Agile methodologies.
• Strong problem-solving and communication skills., * Experience with Azure OpenAI or OpenAI APIs.
• Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• Experience with vector databases/search platforms such as Azure AI Search, Pinecone, FAISS, or similar technologies.
• Knowledge of AI agents and agentic workflows.
• Experience with Docker and Kubernetes.
• Familiarity with MLOps/LLMOps concepts.
• Experience with AI evaluation, guardrails, and responsible AI.
• Experience working with enterprise data or regulated industries such as banking, financial services, or insurance., * 3-6 years of total technology experience.
• 2+ years of hands-on experience with AI/ML or Generative AI is preferred.