Job Title: Generative AI / LLM Engineer
Experience: 5+ years
Education: 15 years of full-time education Role Overview
We 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 Responsibilities
- Design 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 Skills
- 5+ 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 Have
- Experience 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.
Education
- Minimum 15 years of full-time education.