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Open nowPosted 17 days ago

Senior Generative AI Application Engineer_ Contract

MyCareersFuture94,028 open roles

Pay
SGD 7,000 – SGD 10,500 a month
Where
Central, Singapore
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Your applicationOpen nowSenior Generative AI Application Engineer_ ContractMyCareersFuture · Central, Singapore

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This job: posted 17 days ago

The posting

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 [email protected]

We look forward to your application!

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