Senior GenAI Application Engineer

Responsibilities:We are looking for a Senior GenAI Application Engineer who operates effectively at the intersection of software engineering, GenAI application development, enterprise integration and production delivery.This is not a pure research role. It is not a prompt engineering only role. The successful candidate will help design, build and improve production grade GenAI applications that are reliable, observable, maintainable and useful to real enterprise users.The successful candidate will: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.Bring a strong can do attitude, enthusiasm, curiosity and practical delivery mindset.Finance or banking experience is not required. What matters more is hands on experience building real GenAI applications, strong engineering judgement and the ability to deliver in a complex enterprise environment.Requirements: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.Good understanding of API design, distributed systems and production resilience patterns.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 codeStrong analytical, debugging and troubleshooting skills.High ownership, high curiosity and genuine interest in building useful AI products.Ability to work in a fast moving environment with incomplete information and evolving requirementsKey Domain/ Technical Skills·      Production GenAI Application Engineering·      LangGraph, LangChain, RAG and Agentic WorkflowsPython, Java, APIs and Enterprise Integration