Kryptos Technologies UK Limited
Agentic AI Engineer
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Agentic AI Engineer
Duration: 3-4 months
Location: London
Role Summary
We are seeking a highly skilled AWS AI Agent Engineer with strong hands-on experience in agentic AI development, Amazon Bedrock, AWS AgentCore, Python, TypeScript and production-grade AIOps. The role will focus on designing, building, deploying and operating enterprise AI agents and multi-agent workflows on AWS, with strong emphasis on observability, reliability, cost control, security and continuous optimization in production environments.
Required Skills
Agentic AI, Engineering, AWS Platform, AIOps/LLMOps, Dev
Key Responsibilities
AI Agent Development
- 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.
Application Engineering
- 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.
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AIOps, Production Monitoring & Operations
- 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.
DevOps & Platform Collaboration
- 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.
Requirements
Required Skills & Qualifications
- Strong hands-on experience in Amazon Bedrock and agentic AI implementation patterns.
- Practical experience with AWS AgentCore or similar AI agent runtime/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.
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Preferred Skills
- Experience with LangChain, LangGraph, Semantic Kernel, CrewAI or similar agent frameworks.
- Experience with Bedrock Knowledge Bases, vector databases such as OpenSearch, Pinecone or Weaviate, and embedding-based retrieval patterns.
- Experience with MCP (Model Context Protocol), enterprise tool integration and workflow automation.
- Knowledge of AI safety, guardrails, governance, responsible AI and GenAI FinOps.
- Experience integrating AI solutions with ServiceNow, Salesforce, SAP or other enterprise systems.
- Experience operating highly available AI applications in production environments.
Certifications
- AWS Certified AI Practitioner – preferred.
- AWS Certified Machine Learning Engineer – preferred.
- AWS Certified Developer Associate – preferred.
- AWS Certified Solutions Architect Associate or Professional – preferred.
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