AI/Platform Engineer - AWS Bedrock Agentcore

About the role

This position focuses on transforming AI prototypes into production-ready systems. You will be instrumental in building and deploying advanced conversational AI, RAG pipelines, and agent architectures that serve live users. Your work will bridge the gap between experimental AI and reliable, scalable applications.

Key facts

What you'll do

• Develop and deploy AI-powered conversational systems and agents.
• Engineer and launch production-grade Retrieval-Augmented Generation (RAG) systems.
• Build and deploy large language model applications on platforms like AWS Bedrock or Azure OpenAI.
• Orchestrate agent architectures using frameworks such as LangChain or LlamaIndex.
• Create and maintain integrations for extended agent functionality.
• Design and implement the production service layer using AWS services like Lambda and API Gateway.
• Establish continuous integration and continuous deployment (CI/CD) pipelines.
• Implement comprehensive observability, including tracing, metrics, and audit trails.
• Integrate essential security controls for data protection and access management.
• Write production-quality Python code for both AI applications and platform components.
• Monitor, evaluate, and refine the performance of AI systems in a live environment.
• Stay informed about advancements in LLMs and cloud AI platforms, applying them to the project.

Requirements

• Demonstrated experience building production-level conversational AI systems or AI platform infrastructure.
• Practical experience with LLM application platforms such as AWS Bedrock or Azure OpenAI.
• Strong proficiency in Python for AI development and service integration.
• Hands-on experience with either AWS or Azure cloud environments.
• Experience with at least one of the following: agent orchestration frameworks (LangChain, LangGraph, LlamaIndex), RAG system design, or AWS production infrastructure (Lambda, API Gateway, IAM, DynamoDB, OpenSearch).
• Experience with monitoring and observability for AI or distributed systems.
• Solid understanding of security, data handling, and production readiness considerations.
• Adaptability to a rapidly evolving technical landscape and sound engineering judgment.

Nice to have

• Experience with Model Context Protocol (MCP) servers.
• Familiarity with infrastructure-as-code tools like CDK or CloudFormation.
• Experience with distributed data processing tools such as Apache Spark.
• Experience with ML platforms like Amazon SageMaker.
• Experience managing OpenSearch for RAG workloads.
• Experience building data pipelines for AI evaluation.
• Comfort working in an AI-assisted development environment.

Skills & tools

• Python
• AWS Bedrock
• Azure OpenAI
• LangChain
• LangGraph
• LlamaIndex
• AWS (Lambda, API Gateway, IAM, DynamoDB, OpenSearch)
• Azure
• RAG
• Conversational AI
• AI Agents
• CI/CD
• Observability
• Monitoring
• Security

Practical notes

• Rate: $30-$50 per hour.
• Application deadline: August 12th, 2026.