About the role

This is a Full Stack Engineer (Consultant) role focused on maintaining and evolving an existing AI-powered application (Chatbook), ensuring stability, performance, and continuity of service. You will design and build new AI solutions leveraging large language models, retrieval-augmented generation, and agentic frameworks, working closely with Project Managers, Solution Architects, and business stakeholders to deliver production-grade AI applications on AWS.

Key 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 area

Maestro HR

damien lee tian hong

R1106726

16C8462