Senior Generative AI Application Engineer_ Contract

Job title: Senior Generative AI Application Engineer Position level: Professional / Senior Executive Employment type: Contract , Contract duration: 12 months renewable Working location : Singapore CBD in 2026; PDD from 2027 Our client is a leading bank in Asia with an established international network across Asia Pacific, Europe and North America. This is a hands-on engineering position operating at the intersection of software engineering, Generative AI application development, enterprise integration and production delivery. This is not a pure research, data science or prompt-engineering-only role. The successful candidates will design, build, deploy and enhance production-grade GenAI applications that are reliable, observable, secure, maintainable and useful to enterprise users. Key Responsibilities • Design, develop and enhance production-grade Generative AI applications. • Build GenAI solutions using LangGraph, LangChain or comparable orchestration frameworks. • Develop retrieval-augmented generation pipelines, agentic workflows, tool-calling capabilities, prompt orchestration and context-management solutions. • Integrate hosted and open-weight large language models into enterprise applications. • Connect GenAI applications with APIs, backend services, databases, document repositories, enterprise data sources and operational platforms. • Build reliable backend services using Python, Java or comparable programming languages. • Design and implement model-routing, retrieval, caching, conversation-state and fallback mechanisms. • Establish application logging, tracing, monitoring, evaluation and troubleshooting capabilities. • Develop automated evaluation frameworks to measure retrieval quality, response accuracy, reliability and application performance. • Deploy and operate GenAI workloads within Kubernetes, OpenShift or similar containerised environments. • Apply appropriate security, access-control and data-protection measures to enterprise AI solutions. • Troubleshoot complex application, model, integration and infrastructure issues. • Write clean, maintainable, reusable and testable production code. • Review technical designs, challenge unsuitable approaches and recommend practical improvements. • Collaborate with business, application, data, platform, infrastructure, architecture and cybersecurity teams. • Support applications through development, testing, deployment, production stabilisation and continuous improvement. Requirements • At least 5 years of software engineering, application development or closely related technical experience. • Recent hands-on experience designing and building Generative AI applications. • Proven experience delivering production-grade GenAI applications—not only demonstrations, proofs of concept or academic projects. • Strong practical experience with LangGraph, LangChain or comparable LLM orchestration frameworks. • Hands-on experience with RAG, agentic workflows, tool calling, prompt orchestration and context management. • Experience integrating LLMs with real applications through APIs, backend services and enterprise data sources. • Strong backend engineering skills using Python, Java or similar languages. • Good understanding of REST APIs, distributed systems and production-resilience patterns. • Experience designing retrieval pipelines involving document parsing, chunking, embeddings, vector search, reranking and cited generation. • Practical experience with observability, logging, tracing, evaluation and troubleshooting for GenAI or backend applications. • Familiarity with Docker and container orchestration platforms such as Kubernetes or OpenShift. • Understanding of application security, access controls and responsible handling of enterprise information. • Strong analytical, debugging and problem-solving capabilities. • Ability to work effectively with incomplete information and evolving requirements. • Strong ownership, curiosity and genuine interest in building useful AI products. • Good communication skills and the confidence to challenge weak technical designs. • Ability to coordinate effectively across business and multidisciplinary technology teams. Banking or financial-services experience is advantageous but not mandatory. Strong GenAI application engineering and practical production-delivery experience are more important. Good-to-Have Experience • Open-weight models such as Llama, Mistral, Qwen or comparable models. • vLLM or similar model inference and serving frameworks. • DeepAgent or comparable agent frameworks. • Langfuse or similar LLM observability and evaluation platforms. • Elasticsearch or similar enterprise search technologies. • Redis for caching, conversation state, rate limiting, pub/sub or queue-backed workflows. • Vector databases and hybrid retrieval approaches. • Model Context Protocol integrations. • Cloud-based GenAI services and deployment platforms. • CI/CD pipelines for AI and backend applications. Interested candidates are kindly requested to email their CV with their experience to sandeep.sringeripai@global.ntt We look forward to your application!