Full-Stack Developer (AMK)
Posted Updated
Summary
Maintain and evolve an AI-powered application and build new AI solutions using LLMs, RAG, and agentic frameworks on AWS. Stack includes Python, Next.js, React, and AWS Bedrock.
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.
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
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
What they ask for
Required
- Working experience building AI agents and multi-agent systems
- Experience with frameworks like LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI
- Working experience with MCP-based tool integrations
- Experience maintaining GenAI and agentic applications in production
- Knowledge of LLMOps practices including prompt management and observability
- Strong fundamentals in clean code, design patterns, and testing
- Experience with REST API, containerisation, and CI/CD
- Proficiency in Next.js and React
- Proficiency in Python, TypeScript, and Tailwind CSS
- Proficiency in relational and NoSQL databases
- Familiarity with vector databases
- Working experience with AWS platform
- Hands-on experience with AWS Bedrock
Preferred
- Experience developing on Government Commercial Cloud (GCC)
Skills
- Agentic AI
- AI
- Anthropic
- API
- AutoGen
- AWS
- AWS Bedrock
- CI/CD
- Claude
- Cloud
- CloudWatch
- Containerization
- CrewAI
- CSS
- Design Patterns
- Generative AI
- IAM
- Lambda
- LangChain
- LangGraph
- LangSmith
- LlamaIndex
- LLM
- LLMOps
- MCP
- Model Evaluation
- Next.js
- NoSQL
- Observability
- Python
- RAG
- React
- REST
- Semantic Search
- Serverless
- Tailwind
- TypeScript
- Vector Databases