Senior GenAI Application Engineer

We are seeking an experienced AI Engineer to design, develop and deploy production-grade Generative AI applications within an enterprise environment.The successful candidate will have strong software Engineering fundamentals and hands-on experience with Large Language Models (LLMs), LangGraph, LangChain, Retrieval-Augmented Generation (RAG) and agenticAI workflows.This role focuses on building scalable, reliable and maintainable GenAI applications, integrating AI capabilities with enterprise systems and delivering practical AI solutions for business users.Key ResponsibilitiesDesign, develop and enhance production-grade Generative AI applications using frameworks such as LangGraph, LangChain or similar orchestration tools.Build and implement Agentic AI workflows, Retrieval-Augmented Generation (RAG), tool calling, prompt orchestration and context management solutions.Integrate Large Language Models (LLMs), including open-weight and hosted models, into enterprise applications and backend services.Develop scalable backend services and REST APIs using Python, Java or other relevant programming languages.Integrate GenAI applications with enterprise systems, databases, APIs, internal data sources and operational platforms.Implement production-level capabilities including logging, monitoring, tracing, evaluation, error handling and fallback mechanisms.Work with platform and infrastructure teams to deploy and maintain GenAI applications in containerized environments such as Kubernetes or OpenShift.Troubleshoot application issues, optimize performance and improve the reliability, scalability and maintainability of GenAI solutions.Collaborate with application, data, security, infrastructure and business teams to translate business requirements into practical AI solutions.Evaluate emerging GenAI technologies, frameworks and model-serving approaches to continuously improve application capabilities.RequirementsMinimum 6 years of experience in software engineering, backend development or application engineering, with recent hands-on experience in GenAI application development.Proven experience developing and deploying production-grade GenAI applications beyond prototypes, proof of concepts or experimental projects.Strong hands-on experience with LangGraph, LangChain or similar LLM orchestration frameworks.Practical experience in RAG, Agentic AI, tool calling, prompt engineering, prompt orchestration and context management.Strong understanding of Large Language Models (LLMs), including hosted models and open-weight models.Proficiency in Python, Java or similar programming languages, with strong backend development capabilities.Experience developing and integrating REST APIs, backend services, enterprise applications and external data sources.Good understanding of distributed systems, application architecture, API design and production resilience patterns.Experience with application observability, logging, tracing, testing, debugging and performance optimization.Familiarity with containerization and deployment technologies such as Docker, Kubernetes or OpenShift.