Full-Stack Developer (AMK)

About the role

Maintain and evolve an existing AI-powered application (Chatbook), ensuring stability, performance, and continuity of service. Design and build new AI solutions leveraging large language models, retrieval-augmented generation, and agentic frameworks. Work closely with Project Managers, Solution Architects, and business stakeholders to deliver production-grade AI applications on AWS.

Responsibilities

• Take over the Chatbook Application through structured knowledge transfer, documenting existing architecture, codebase, and integrations
• Perform ongoing system maintenance including updates, bug fixes, performance tuning, and incident resolution
• Design and develop end-to-end AI solutions using LLMs, RAG architectures, and agentic frameworks
• Build MCP-based tool integrations and agentic pipelines for enterprise system connectivity
• Implement monitoring and observability for AI model performance and agentic behaviour
• Translate business and stakeholder requirements into robust, AI-powered solutions
• About you
• Working experience building AI agents and multi-agent systems using frameworks such as LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI, with a strong understanding of agentic design patterns including planning, tool use, memory, and reflection
• Working experience with MCP-based tool integrations and maintaining GenAI and agentic applications in production environments, including guardrail implementation and application evaluation
• Knowledge of LLMOps practices, including prompt management, model evaluation, LLM observability tools (e.g. LangSmith), AI governance, and responsible AI principles
• Strong fundamentals encompassing clean code, design patterns, testing, REST API development, containerisation, container orchestration, and CI/CD pipelines
• Proficiency in Next.js / React, Python, TypeScript, and Tailwind CSS
• Proficiency in relational and NoSQL databases covering query optimisation, schema design, and data management, with familiarity with vector databases for RAG and semantic search
• Working experience with AWS cloud platform including serverless services (Lambda, API Gateway), storage (S3), monitoring (CloudWatch), and access management (IAM)
• Hands-on experience with AWS Bedrock to access and orchestrate foundation models such as Anthropic Claude, including features such as Knowledge Bases, Agents, and Guardrails for production-grade generative AI applications
• Experience developing and deploying applications on Government Commercial Cloud (GCC) is an advantage
• 5 day week @ AMK
• Maestro HR
• damien lee tian hong
• R1106726

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