Generative AI

About this opportunity

Role Overview We are looking for an experienced Generative AI / LLM Engineer to design, develop, and deploy AI-powered applications and solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and modern AI frameworks. The ideal candidate will have strong hands-on experience in Python, LLMs, RAG, prompt engineering, AI application development, APIs, and cloud-based AI platforms . Experience with production-grade GenAI solutions and enterprise applications will be highly preferred. Key Responsibilities Design and develop enterprise-grade Generative AI and LLM-based applications . Build and deploy RAG-based solutions using enterprise and unstructured data. Develop AI agents and multi-step AI workflows for business use cases. Integrate LLMs with enterprise applications, APIs, databases, and external services. Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini , or equivalent. Develop prompt engineering strategies and optimize model responses. Implement vector search and semantic retrieval using vector databases. Develop APIs and backend services for AI applications. Evaluate LLM performance, accuracy, hallucination, latency, and cost. Implement techniques for improving response quality and context retrieval. Collaborate with Data Scientists, Data Engineers, Software Engineers, Architects, and business stakeholders. Deploy AI solutions on cloud platforms and support production environments. Implement monitoring, logging, security, and governance for AI applications. Stay updated with emerging developments in GenAI, Agentic AI, LLMs, and AI engineering . Mandatory Skills Strong programming experience in Python . Hands-on experience with Generative AI / LLM applications . Strong understanding of Large Language Models (LLMs) . Experience building RAG pipelines . Experience with Prompt Engineering . Experience working with LLM APIs such as OpenAI/Azure OpenAI or equivalent. Experience with AI/ML frameworks and libraries. Strong knowledge of REST APIs and backend application development. Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus, or Chroma . Strong understanding of embeddings, semantic search, context retrieval, and tokenization. Good knowledge of SQL and databases. Experience deploying applications on AWS, Azure, or GCP . Good-to-Have Skills Experience with Agentic AI and autonomous AI workflows. Experience with LangChain / LangGraph / LlamaIndex . Knowledge of Model Context Protocol (MCP) . Experience with Azure OpenAI and Azure AI services. Experience with Databricks. Knowledge of MLOps / LLMOps . Experience with Docker and Kubernetes. Knowledge of CI/CD pipelines. Experience with model evaluation frameworks. Knowledge of AI security, responsible AI, and data privacy. Experience integrating GenAI with enterprise systems such as CRM, ERP, ITSM, or workflow platforms. Preferred Technology Stack Languages: Python, SQL AI/LLM: OpenAI, Azure OpenAI, Llama, Mistral, Gemini Frameworks: LangChain, LangGraph, LlamaIndex Vector Databases: Pinecone, FAISS, Weaviate, Milvus, Chroma Cloud: AWS / Azure / GCP DevOps: Docker, Kubernetes, Git, CI/CD Data: Databricks, Spark, SQL Education Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related discipline . Candidate Profile The ideal candidate should: Have strong problem-solving and analytical capabilities. Be comfortable working on rapidly evolving AI technologies. Have experience taking AI/LLM solutions from POC to production . Understand both the technical and business aspects of GenAI implementations. Have strong communication and stakeholder-management skills. Be comfortable working in a client-facing environment.