LLM Application Lead

Job Title: Generative AI / LLM EngineerExperience: 5+ yearsEducation: 15 years of full-time education Role OverviewWe are looking for a Generative AI / LLM Engineer with 5+ years of experience to design, develop, and deploy AI solutions powered by Large Language Models. The role involves building LLM-based applications, integrating AI services with enterprise systems, and developing scalable solutions using modern Generative AI technologies.Key ResponsibilitiesDesign and develop LLM and Generative AI applications for enterprise use cases. Build solutions using LLMs, prompt engineering, RAG, embeddings, and vector databases. Integrate LLM capabilities with existing applications, APIs, and enterprise platforms. Develop and optimize prompts, workflows, and model responses for accuracy and performance. Implement RAG pipelines for knowledge retrieval and context-aware responses. Evaluate LLM outputs and improve solution quality, reliability, and scalability. Work with data and engineering teams to prepare and integrate relevant datasets. Deploy and monitor GenAI/LLM solutions across development and production environments. Troubleshoot technical issues and continuously improve AI applications. Collaborate with business and technical stakeholders to translate requirements into AI solutions. Required Skills5+ years of experience in AI/ML or software engineering, with strong hands-on experience in LLM/Generative AI. Strong knowledge of Large Language Models (LLMs) and Generative AI concepts. Hands-on experience with Prompt Engineering, RAG, embeddings, and vector databases. Experience with LLM frameworks/tools such as LangChain, LlamaIndex, or similar. Experience working with commercial or open-source LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, Llama, or similar. Strong Python programming and API integration skills. Understanding of ML/AI model evaluation, deployment, and monitoring. Good knowledge of cloud platforms such as Azure, AWS, or GCP. Strong problem-solving and communication skills. Good to HaveExperience with fine-tuning or adapting LLMs for domain-specific use cases. Knowledge of AI agents, tool calling, and multi-agent workflows. Experience with MLOps/LLMOps and production-scale AI deployments. Knowledge of NLP and transformer architectures. EducationMinimum 15 years of full-time education.