Demonstrates expertise in designing and deploying scalable AI applications using Large Language Models, with a strong focus on backend development, API integration, and performance optimization. Proficient in leveraging modern AI frameworks and cloud infrastructure to deliver production-ready solutions.

Highest-signal resume keywords

Python ProgrammingBackend Development FrameworksLLM API IntegrationAI Application Performance OptimizationCloud Infrastructure Management

Tech Stack

Tools & technologies

AWSCloudDjangoDockerPython

About the role

Key responsibilities & impact

Design, develop, and deploy scalable, secure, and production-ready AI applications using Large Language Models and modern AI frameworks
Build AI agents and automated workflows integrating APIs, databases, tools, and existing systems
Develop and optimize Retrieval-Augmented Generation pipelines, including document processing, embeddings, vector search, and retrieval strategies
Integrate and manage LLM providers such as OpenAI, Anthropic, and AWS Bedrock using prompt engineering, structured outputs, and function calling
Develop and maintain backend services and RESTful APIs
Implement AI evaluation frameworks and guardrails for accuracy, consistency, safety, reliability, sensitive-data protection, and human escalation
Optimize AI application performance, response latency, token usage, and infrastructure costs
Deploy, monitor, and maintain AI services using cloud infrastructure, Docker, and CI/CD pipelines
Collaborate with product, engineering, and clinical teams to translate business requirements into AI-powered solutions
Research and evaluate emerging AI technologies, models, and frameworks

Requirements

What you’ll need

Degree in Computer Science, Engineering, or a related field
4+ years of professional software engineering experience, including practical experience building AI/LLM applications
Strong proficiency in Python and backend development frameworks such as FastAPI or Django
Hands-on experience integrating LLM APIs, including OpenAI, Anthropic, or similar providers
Experience building production-oriented LLM applications using prompting, structured outputs, and tool/function calling
Practical experience with AI agents and agentic workflows, including frameworks such as LangGraph, LangChain, or equivalent approaches
Solid understanding of RAG architectures, embeddings, retrieval techniques, and vector databases such as pgvctor, Pinecone, Milvus, or similar
Understanding of AI evaluation, automated testing, hallucination mitigation, and prompt-injection risks
Experience with agentic AI architectures, agent harnesses, and iterative execution loops, including tool orchestration, feedback loops, state management, and automated validation
Experience designing RESTful APIs, integrating databases, and developing backend services
Hands-on experience with AWS, Docker, and cloud infrastructure
Familiarity with CI/CD pipelines, Git, and application monitoring
Knowledge of application security, data privacy, and responsible AI development
Strong problem-solving skills and ability to independently deliver AI features from prototype to production
Must be able to work in Malaysia/Singapore time (GMT+8)
Must be proficient in English, with strong written and verbal communication skills
Visa sponsorship is not available

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Large Language ModelsAI Application DevelopmentRetrieval-Augmented GenerationRESTful API DesignDocument ProcessingEmbeddingsVector SearchAutomated TestingApplication SecurityData Privacy

Soft Skills

Problem-SolvingCommunication Skills

Tools & Technologies

FastAPIDjangoAWSDockerCI/CD PipelinesGitLangGraphLangChainPineconeMilvus

Industry Keywords

AI Evaluation FrameworksAutomated WorkflowsAgentic AI ArchitecturesSensitive-Data ProtectionHuman Escalation