Senior GenAI Engineer

Responsibilities:Build and improve GenAI applications using frameworks such as LangGraph, LangChain or similar orchestration tools. Work with open weight models, hosted LLMs and model serving patterns.Develop agentic workflows, retrieval augmented generation, tool calling and prompt orchestration.Integrate GenAI applications with enterprise systems, APIs, data sources and operational platforms.Engineer solutions for production quality, including logging, tracing, evaluation, fallback behaviour and troubleshooting. Strong hands on experience building production grade GenAI applications. Practical experience with LangGraph, LangChain, agentic workflows, RAG and tool calling. Understanding of open weight models and how to integrate them into real applications. Ability to challenge weak designs and propose better ones. Strong engineering discipline around reliability, testing, observability and maintainability. Ability to work across application, data, platform, security and infrastructure teams.Requirement: 10 or more years of software engineering experience, preferably with recent hands on experience in GenAI application development. Proven experience building production grade GenAI applications, not only prototypes, experiments or demos. Strong hands on experience with LangGraph, LangChain or similar orchestration frameworks. Practical understanding of RAG, agentic workflows, tool calling, prompt orchestration and context management.Experience integrating LLMs into real applications using APIs, backend services and enterprise data sources. Experience with open weight models or strong interest backed by hands on experimentation. Strong backend engineering skills using Python, Java or similar languages. Experience with observability, logging, tracing and troubleshooting for GenAI or backend applications.Familiarity with containerised deployment environments such as Kubernetes or OpenShift. Ability to write clean, maintainable and testable code. Strong analytical, debugging and troubleshooting skills. High ownership, high curiosity and genuine interest in building useful AI products.