Data Engineer

7 hours ago

Kuala Lumpur, Kuala Lumpur, Malaysia Sciente International Pte Ltd Full time $120,000 - $200,000 per year

Job Summary:

We are seeking a highly skilled Senior GenAI Platform Engineer who can independently manage the full lifecycle of Generative AI (GenAI) solution development -from model selection and fine-tuning to backend integration and production deployment. This role requires a hybrid skillset across GenAI solution engineering, backend development, and Site Reliability Engineering (SRE), ensuring robust, scalable, and reliable GenAI solutions fully integrated with core banking and enterprise systems.

Mandatory Skill-set

  • Must have 3–5 years of hands-on experience in developing, fine-tuning, and deploying GenAI/LLM applications (OpenAI, Anthropic, Gemini, Llama, etc.);
  • Must have hands on experience with RAG pipelines and frameworks like LangChain, LlamaIndex, or Hugging Face Transformers;
  • Must have hands on experience with Docker, Kubernetes, and Terraform for containerization, orchestration, and infrastructure automation;
  • Hands on experience with LLMOps and SRE principles — including reliability, scalability, monitoring, and performance optimization;

    Proven experience implementing CI/CD pipelines (GitLab CI, Jenkins, or similar tools);
  • Strong backend development skills using Python, Golang, or (API and microservices);
  • Proficiency in backend development using Python, Golang, or (API and microservices);
  • Experience in setting up and maintaining CI/CD pipelines using GitLab CI, Jenkins, or similar tools.

Desired Skill-set

  • Experience in cloud environments such as AWS, GCP, or Azure;
  • Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) for context retrieval;
  • Working knowledge of banking system integrations, especially core banking or CRM platforms;
  • Exposure to API Gateway management and secure data exchange protocols;
  • Background in CI/CD pipeline design using GitLab CI, Jenkins, or similar tools.

Responsibilities

  • Lead the end-to-end design, development, and deployment of GenAI solutions integrated with enterprise systems;
  • Build and optimize RAG pipelines and backend services powering GenAI capabilities;
  • Develop microservices and APIs to integrate AI functionalities within core banking or enterprise applications;
  • Design and implement LLM observability and performance monitoring frameworks;
  • Automate and manage infrastructure through Terraform, Docker, and Kubernetes;
  • Set up and maintain Model Context Protocol (MCP) servers for efficient context streaming;
  • Implement LLMOps best practices for continuous monitoring, versioning, and retraining of models;
  • Define and manage CI/CD pipelines for infrastructure, backend code, and GenAI models;
  • Ensure system reliability, scalability, and cost optimization across environments;
  • Collaborate cross-functionally with business, data, and IT teams to ensure smooth solution delivery.

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