AWS AI Agent Engineer

Salary: £? - ? per year

Requirements:

• Strong hands-on experience in Amazon Bedrock and agentic AI implementation patterns.
• Practical experience with AWS AgentCore or similar AI agent runtime and orchestration capabilities.
• Advanced Python and TypeScript development experience.
• Experience implementing RAG, prompt engineering, tool/function calling, and AI workflow orchestration.
• Experience with production monitoring, observability, and operational support for AI/ML or GenAI workloads.
• Strong understanding of AWS serverless, event-driven architecture, IAM, and cloud security principles.
• Good understanding of CI/CD, Infrastructure as Code, and release automation.
• Strong problem-solving, communication, and stakeholder collaboration skills.
• Experience with LangChain, LangGraph, Semantic Kernel, CrewAI, or similar agent frameworks is preferred.
• Experience with Bedrock Knowledge Bases, vector databases such as OpenSearch, Pinecone, or Weaviate, and embedding-based retrieval patterns is preferred.
• Experience with MCP, enterprise tool integration, and workflow automation is preferred.
• Knowledge of AI safety, guardrails, governance, responsible AI, and GenAI FinOps is preferred.
• Experience integrating AI solutions with ServiceNow, Salesforce, SAP, or other enterprise systems is preferred.
• Experience operating highly available AI applications in production environments is preferred.
• AWS certifications in AI, machine learning, development, or solutions architecture are preferred.

Responsibilities:

• Design and develop AI agents and multi-agent workflows using AWS AgentCore and Amazon Bedrock.
• Build autonomous and intelligent agents leveraging foundation models, tools, memory, and orchestration capabilities.
• Implement RAG, tool calling, agent collaboration patterns, and workflow automation for enterprise use cases.
• Integrate AI agents with enterprise APIs, databases, event streams, and third-party platforms.
• Design secure and scalable AI architectures aligned to AWS Well-Architected principles.
• Develop backend services, APIs, and orchestration components using Python and TypeScript.
• Build event-driven and serverless applications using AWS Lambda, API Gateway, EventBridge, Step Functions, DynamoDB, and SQS/SNS.
• Create reusable libraries, patterns, and accelerators to standardize AI agent development across teams.
• Establish monitoring, observability, and operational governance for production AI workloads.
• Track agent performance, model latency, cost, prompt effectiveness, error rates, and quality signals.
• Define alerting, incident response, RCA processes, and production runbooks for AI applications.
• Troubleshoot AI agent issues across orchestration logic, integration failures, prompt/model behavior, and platform dependencies.
• Continuously optimize reliability, accuracy, latency, and cost for production GenAI systems.
• Build and maintain CI/CD pipelines for AI application and agent deployments.
• Implement Infrastructure as Code using Terraform, AWS CDK, or CloudFormation.
• Collaborate with solution architects, platform teams, security teams, and business stakeholders to deliver enterprise-grade AI solutions.

Technologies:

• Agentic AI
• AI
• AI Agents
• API
• AWS
• Lambda
• OpenSearch
• Backend
• CI/CD
• Cloud
• IAM
• Support
• Machine Learning
• MCP
• Python
• RAG
• SAP
• Salesforce
• Security
• Serverless
• ServiceNow
• Terraform
• TypeScript
• Architect
• CloudWatch
• DevOps
• Docker
• GitHub
• GitLab
• Incident Management
• REST

More:

We are hiring an AWS AI Agent Engineer for a 3–4 month engagement in London. This is an outside IR35 contract at a rate of £400 per day. We are looking for someone to help design, build, deploy, and operate enterprise AI agents and multi-agent workflows on AWS, with a strong focus on observability, reliability, cost control, security, and continuous optimization in production environments.

last updated 34 week of 2026